Introduction
Definition and Classification of Biomedical Sensors
Biomedical sensors are crucial devices that convert non-electrical signals into electrical signals This article will provide an overview of biomedical sensors, including their definition and classification.
A sensor, also known as a transducer, is a device that detects a measured object and converts it into detectable signals Typically, a sensor consists of a sensitive component that directly interacts with the object, a conversion component, and associated electronic circuits With advancements in modern electronic, micro-electronic, and communication technologies, electrical signals have become the most efficient format for processing, transporting, displaying, and recording various useful signals.
Sensors are devices that convert non-electrical signals into electrical signals, providing crucial information about the physical, chemical, or biological state of a system Measurement is the process of obtaining the value of a specific quantity, and sensor detection technology utilizes sensors to transform these measured quantities into physical forms that facilitate communication and processing This technology encompasses various functions, including transformation, communication, display, recording, and analysis of data.
Biomedical sensors are electronic devices that convert non-electrical quantities in the biomedical field into detectable electrical signals, making them essential for healthcare analysis These sensors enhance the capabilities of human sensory organs and are integral components of diagnostic medical instruments and equipment Biomedical sensing technology plays a crucial role in gathering human physiological and pathological data, establishing itself as a vital branch of study in the medical field.
Biomedical sensors can be classified in the following categories according to their detection quantities Classified by working principle, sensors include physical sensors, chemical sensors, and biological sensors
Physical sensors are devices designed based on physical principles and effects, including various types such as metal resistance strain sensors, semiconductor piezoresistive sensors, piezoelectric sensors, and photoelectric sensors.
Chemical sensors are devices designed based on their chemical properties and effects, utilizing ion-selective sensitive films to convert non-electrical measurements—such as chemical composition, concentration, and density—into related electrical signals Common examples include various ion-sensitive electrodes, ion-sensitive tubes, and humidity sensors.
Biological sensors, or biosensors, utilize biologically active materials as molecular recognition systems, often employing enzymes to catalyze biochemical reactions or analyze large organic molecules through specific interactions Developed in the latter half of the 20th century, these innovative sensors include various types such as enzyme sensors, microorganism sensors, immunity sensors, tissue sensors, and DNA sensors.
Detection types of sensors include displacement, flow, temperature, speed, and pressure sensors Pressure sensors can be categorized into metal strain foil, semiconductor, and capacitive types Temperature sensors encompass thermal resistance and thermocouple sensors.
PN junction temperature sensors are part of a broader category of sensors that detect temperature These sensors can be classified based on the human senses they emulate For instance, vision sensors encompass various optical sensors that replicate visual functions, while hearing sensors include sound pick-up devices, piezoelectric sensors, and capacitive sensors that mimic auditory capabilities Additionally, olfactory sensors consist of various gas sensors designed to substitute for the sense of smell.
2000) This kind of classification is good for the development of simulation sensors
In various applications, classification methods are often utilized in combination, such as with strain gauge pressure sensors, conductance cardiac sound sensors, and thermoelectric glucose sensors However, the rapid advancements in sensing technology have led to challenges in classification Each classification method presents its own set of advantages and disadvantages, and currently, there is no universally accepted standard classification method available.
Biomedical Measurement Technology
Biomedical signals are often weak and random, characterized by strong noise and interference, which leads to dynamic changes and notable individual variations Consequently, the technologies used for biomedical measurement are more complex and rigid compared to standard industrial detection technologies.
Biomedical measurement plays a crucial role in acquiring and processing biomedical information, closely linked to the advancement of biomedical sensing technology, measurement methods, electronics, and measuring systems Consequently, innovative research and development in this field significantly influences the design and application of sensors and medical instruments.
Biomedical measurement technology focuses on detecting various physical, chemical, and biological signals across different organisms Key examples include electrical physiological signals like ECG, EEG, and EMG, as well as non-electrical signals such as blood pressure, body temperature, respiration, blood flow, and pulse Additionally, chemical and biological signals are represented by blood and urine, while enzymes, proteins, antibodies, and antigens serve as critical biological indicators Ensuring high reliability and security is essential for biomedical measurement systems.
The measurement of physical and chemical signals has gained popularity, while biological signal measurement is primarily in the laboratory research phase The integration of microelectronics, optoelectronics, quantum chemistry, and molecular biology with traditional sensing technologies promises a bright future for detecting complex organisms Furthermore, biomedical measurement technology is evolving towards miniaturization, multi-parameter capabilities, and practical applications, driven by advancements in electronics, integrated circuit technology, computer technology, and sophisticated signal processing and intelligent algorithms.
The early and rapid development of physiological quantity detection in the circulatory and nervous systems has sparked extensive research efforts A prime example is the ongoing work by researchers focused on the automatic extraction and discrimination of arrhythmia information from ECG signals, particularly in the presence of strong interference Additionally, significant attention is given to the detection of the P wave in ECG analysis.
Research on the ST segment in ECG has advanced significantly, particularly in obtaining fetal ECG from a mother's body surface, high-frequency ECG, and real-time body surface detection of late potentials ECG technology plays a crucial role in diagnosing heart disease and preventing sudden cardiac death, while also supporting surgical investigative procedures (Tigaran et al.).
2009) Although these research achievements are not mature enough to be put into clinical use, they improve the function of ECG diagnosis and monitoring devices
The biomagnetic field originates from the body's biological electrical activities, including MCG, MEG, and MMG, and is also influenced by external magnetic fields interacting with tissue Additionally, strong invasive magnetic sources can generate internal biomagnetic fields While these biological magnetic fields are typically very weak—around 10^-10 T for MCG and 10^-12 T for MEG—they can be detected in laboratory settings using superconducting quantum interference devices (SQUID) housed in liquid nitrogen containers To ensure accurate measurements, the detection system must be situated in a specially shielded environment.
Biomagnetic field detection offers distinct advantages over bioelectricity detection, exemplified by magnetocardiography (MCG), which utilizes a detecting coil instead of an electrode, ensuring no direct contact with the organism This method eliminates surface interference and electrode artifacts, enhancing electrical safety Additionally, it allows for precise location measurements, as signals originate from specific areas rather than differences between points The well-distributed magnetoconductivity within tissues ensures that biomagnetic signals remain undistorted as they propagate through the body Consequently, research into biomagnetic detection methods is rapidly advancing, showing significant potential for clinical applications, especially with the progress in room temperature superconductor technology.
1.2.3 Other Physiological and Biochemical Parameter Detection
The use of non-invasive sensors for monitoring vital signs such as blood pressure, blood flow, respiration, pulse, body temperature, and cardiac sounds has become increasingly prevalent in clinical settings The focus is shifting towards developing innovative non-invasive or minimally invasive methods that allow a single sensor to capture multiple physiological parameters simultaneously For instance, the photoelectric method can measure pulse rate, blood pressure, and oxygen saturation, while electromagnetic or optical coupling techniques can assess intracranial pressure and oral pressure Additionally, advancements in non-contact and long-distance detection methods are shaping the future of health monitoring technologies.
Biochemical parameter detection traditionally relies on blood and body fluids, making most methods invasive and unsuitable for long-term, real-time monitoring However, there is growing interest in non-invasive and minimally invasive techniques For instance, researchers have successfully detected phenacetin in saliva and validated the results against blood plasma tests Additionally, a method involving the extraction of lixivium through slight negative pressure on the skin has been developed, utilizing ion field effect transistor sensors to measure blood sugar levels Furthermore, dielectric spectroscopy (DS) has been employed to track glucose level fluctuations by integrating electromagnetic and optical sensors (Talary et al., 2007).
Characteristics of Biomedical Sensors and Measurement
Biomedical measurement is crucial for human signal detection, offering a non-invasive, safe, and reliable approach This technology has gained significance in recent years, allowing for easy administration with minimal or no wounds It facilitates the monitoring of physiological status, enabling long-term or real-time assessments, which are essential for clinical examinations, monitoring, and recovery evaluations As a result, non-invasive detection has emerged as a key component of biomedical measurement technology.
Biomedical measurement research employs specialized techniques such as low-noise and anti-interference technology, signal acquisition, and advanced processing systems, including both analog and digital circuits, computer hardware, and software, along with brain-computer interface (BCI) technology This research is closely linked to advancements in life sciences, including cytophysiology, neurophysiology, and biochemistry The wide range of subjects in biomedical detection technology leads to a diverse array of research projects However, improvements in detection methods for physiological and biochemical quantities can significantly drive progress in life sciences and foster the development of innovative diagnostic and treatment devices.
1.3.1 Features of Biomedical Sensors and Measurement
Biomedical sensor technology is an interdisciplinary field that merges electronic science with biomedicine, enabling early and rapid diagnosis, bedside monitoring, and advanced health care This technology is essential for applications such as gene probes, molecular recognition, and the monitoring of neurotransmitters and neuromodulators The advancement of related fields like microelectronics, biological technology, molecular biology, and photonics has significantly contributed to the rapid progress of biomedical sensor technology.
In the 1970s, the integration of sensors into scientific and technological advancements emphasized new product development, focusing on high-level exploration processes Key objectives included understanding molecular recognition mechanisms to enhance signal-to-noise ratios (SNR) and mastering interface processes to reduce response times To translate research findings into viable products, various processing technologies such as precision machining, semiconductor technology, chemical etching, and biotechnology were essential for driving technological innovation.
The core of sensor-sensitive membranes lies in the combination of sensitive materials and matrix materials, utilizing advanced film formation technologies such as semiconductor thin-film and thick-film processes, as well as molecular beam epitaxy for physical sensors Chemical sensors leverage techniques like chemical cross-linking and molecular assembly, while biochemistry-sensitive membranes incorporate multi-enzyme systems, monoclonal antibody films, conductor films, and Langmuir-Blodgett (LB) films Sensor design and production require a multidisciplinary approach; for instance, chemical sensors necessitate knowledge in quantum chemistry for material design, super-molecular and host-slave chemistry for synthesis, and interface chemistry along with precision machining for effective film formation and device transfer.
For biosensors to safely interact with the human body, they must demonstrate high reliability and undergo stringent FDA regulation to ensure long-term safety and accurate monitoring Sensors that detect body fluids should be corrosion-resistant and easy to clean, while embedded or implanted devices must be designed to avoid rejection by the body.
Fine technology is essential for the development of high-precision sensors, particularly in matrix sensors that require specialized implantable technology to prevent leakage or deformation during prolonged immersion The integration of sensitive membranes with fiber cross-sections demands meticulous fine technology, while glass microelectrodes can be manipulated using specific machines Precision machining merges advanced machining techniques with chemical technology, highlighting that sensors are not merely products but also intricate works of art.
1.3.2 Special Requirement of Biomedical Sensors and Measurement
Non-invasive biomedical measurement is a crucial advancement in human signal detection, offering a safe, reliable, and painless method for monitoring physiological status Its ability to facilitate long-term or real-time monitoring makes it an essential tool for clinical examinations and recovery evaluations As a result, non-invasive detection has become integral to biomedical measurement technology, garnering significant attention in recent research.
Biomedical measurement research utilizes specialized methods such as low-noise and anti-interference technology, signal processing, and both analog and digital circuits, alongside advancements in computer hardware and software, including brain-computer interface (BCI) technology The field is closely tied to the life sciences, encompassing areas like cytophysiology, neurophysiology, and biochemistry The diverse range of research subjects in biomedical detection technology leads to a wide array of projects However, enhancing detection methods for physiological and biochemical quantities can significantly drive progress in life sciences and foster the development of innovative diagnostic and therapeutic devices.
When designing biomedical sensors, a key difference from other sensors is the need for biocompatibility, as these sensors interact directly with tissue or blood Therefore, it is essential for the design to incorporate both hemocompatibility and histocompatibility to ensure safety and effectiveness.
The selection of materials is crucial in sensor manufacturing, with inert metals like stainless steel and titanium alloys being essential for durability Additionally, degradable polymers such as PMMA and silicones are preferred to ensure safety It is vital that all materials are carefully chosen to prevent adverse host responses and maintain functionality once implanted in an animal's body Furthermore, the materials must possess the right balance of rigidity and flexibility to adapt to the anatomical structures of the target objects.
Before clinical application, it is essential to conduct a series of animal experiments and clinical trials Despite selecting inert and minimally harmful materials, comprehensive biocompatibility tests are necessary due to the unique physiological environments in which the implanted sensors will operate.
To assess the host response, we utilize biological methods that evaluate in vivo biocompatibility This includes analyzing the cell populations present, measuring the excreted mediators and metabolites, and examining the morphological characteristics of the tissue, as well as the capsule thickness surrounding the implant.
Biological samples, including enzymes, proteins, cells, and tissues, necessitate external analysis, which requires effective immobilization on the sensor surface to preserve their viability and activity Therefore, ensuring biocompatibility is a crucial consideration in the design of in vitro biomedical sensors.
Development of Biomedical Sensors and Measurement
Biomedical sensors and measurements have been developing rapidly over the past
Over the past 30 years, the evolution of medical sensors has transformed traditional practices, leading to trends in smart, micro, multi-parameter, remote-control, and non-invasive technologies Significant technical breakthroughs have been achieved, alongside the development of innovative sensors like DNA sensors, fiber sensors, and biological tissue sensors This revolution in medical sensor technology is poised to advance modern medicine significantly.
1.4.1 Invasive and Non-invasive Detection
The miniaturization of sensors enables direct and continuous monitoring of vascular parameters, such as blood pressure, temperature, and flow rate, emerging as a vital clinical diagnostic tool While commercial products are available, their full potential remains untapped Chemical and biological sensor technologies are crucial for public health, facilitating rapid detection and high sensitivity for healthcare professionals Additionally, clinical doctors require effective methods to monitor key metabolite concentrations related to various diseases, prompting significant advancements in chemical and biological sensors to enhance non-traditional clinical chemistry analysis.
The development of non-invasive detection methods for body fluids is essential, as traditional extraction techniques for fluids like blood, urine, and saliva are often invasive To facilitate continuous monitoring of these fluids, innovative non-invasive or minimally invasive detection technologies must be advanced.
Non-invasive detection means no or nearly no invasion during detection
Non-invasive detection methods are preferred by users due to their minimal impact on the human body and their reliability These methods are easy to operate, facilitate sterilization, and reduce the risk of infection Additionally, non-invasive sensors must exhibit high sensitivity, accuracy, resistance to interference, and an improved signal-to-noise ratio.
Nondestructive monitoring is a highly effective method for patient assessment that has garnered significant interest Recent advancements include percutaneous blood gas sensors capable of non-invasively measuring blood gases such as Po2 and Pco2, as well as innovative non-blood techniques for monitoring vital parameters like blood glucose and urea levels.
International biomedical research sensor technology is synchronous with advances in the development of biomedicine A major issue is how to improve the clinical technology and develop biomedical research
Biosensors are advanced bioanalytical devices that utilize biological materials like proteins, cells, and tissues as sensitive components, combined with physicochemical transducers to detect specific signals Ongoing research in fields such as biomedicine, physics, and nanotechnology has accelerated the development of biosensors, leading to significant applications including micro-structured biomedical sensors and biochips.
In clinical medicine, multi-parameter sensors play a crucial role by integrating various sensitive components onto a single chip, enabling the simultaneous measurement of multiple physiological parameters These compact detection systems offer higher accuracy, enhanced stability, reduced weight, and lower costs compared to traditional multi-sensor setups Additionally, their uniform working conditions facilitate easier compensation and correction of system differences, making them an efficient choice for clinical operations.
Serial operation poses challenges when discrete sensors monitor various parameters, as they lack efficiency and struggle to meet simultaneous time and spatial requirements The advent of integrated technology has paved the way for multi-parameter sensors In the early 1980s, British researchers developed an integrated blood electrolyte sensor that effectively monitors multiple parameters.
5 parameters (Na + , K + , Ca 2+ , Cl – and pH) At the end of the 1980s, some researchers designed LAPS for monitoring multiple biochemical parameters (Wu et al., 2001)
The advancement of living standards today necessitates ongoing improvements in diagnostic and therapeutic methods The integration of MEMS technology is poised to enhance the role of physical sensors in the biomedical field, leading to the creation of smaller, more accurate sensors and innovative measurement techniques As a result, physical sensors are expected to become increasingly miniaturized, precise, integrated, and multifunctional.
1.4.3 In vitro and in vivo Detection
In vivo detection involves assessing the structure and function of living organisms, while in vitro detection focuses on analyzing blood, urine, tissues, or pathological specimens outside of a living organism (Gründler, 2007) These detection technologies are crucial for clinical laboratory tests, enabling the quantitative analysis of substances to determine their normalcy or the presence of pathological microorganisms High accuracy, precision, and rapid response are essential for effective in vitro detection Due to the diverse range of detection categories, various automated detection methods have been developed to optimize sample usage and testing reagents Recent advancements in chemical and biological sensors, alongside improvements in traditional clinical analysis, have significantly enhanced detection capabilities (Wang and Liu, 2009a).
Minim and tracing element detection;
Molecular level and cellular level detecting technology;
Biosensor micro system development and applications;
Detection of olfactory and gustatory quantities
The growing significance of clinical biochemical analysis is driving the evolution of in vitro detection towards multifunctionality, continuous operation, and automation The advancement of computer automated recognition and analysis technology is set to enhance various automatic biochemical detection devices that utilize optical and electrochemical analysis methods.
In vitro detection mostly belongs to the biochemical quantity detection This detection involves many fields including gene engineering, protein engineering,
LB film techniques, biosensor techniques, image analysis process and automatic measurement
In vivo monitoring allows for real-time observation of physiological and pathological processes from a fixed point over extended periods, providing unique insights unattainable by other methods (Hauser and Fhrs, 2009) With advancements in sensor technology, various monitoring options have emerged, including implanted sensors that transmit data from within the body and catheter sensors that continuously measure gases and ions in intravascular blood or the heart However, a significant challenge remains in enhancing the compatibility between these monitoring devices and the organs they interact with (Vo-Dinh and Cullum, 2000).
A brain-computer interface (BCI), also known as a brain-machine interface, facilitates direct communication between the brain and external devices, primarily aimed at enhancing or restoring cognitive and sensory-motor functions In the field of neuroscience, neuroprosthetics focuses on using artificial devices to replace impaired nervous system functions or sensory organs, connecting the nervous system to various devices While neuroprosthetics can interface with any part of the nervous system, BCIs specifically connect the brain or central nervous system to computer systems, highlighting a more specialized application within the broader scope of neuroprosthetics.
A molecular system equipped with sensors can detect proteins, while processors determine gene structures, and actuators can manipulate genes by cutting or joining them This innovative approach allows for the control and modification of genes, potentially influencing life processes The design and synthesis of such molecular systems represent a significant advancement in medicine and pharmacology, particularly in the development of anti-cancer drugs.
Recent research has achieved significant advancements in two key areas: the properties of magnetic waves and infrared light as they pass through skin and human tissue, and the methods for coupling internal and external information One common technique for this information exchange involves an echo response, where energy is implanted for in vivo detection, allowing a controlling device to send detected signals from within the body to the outside for further processing (Ricci, 2010) Alternatively, a stimulus or program-controlled signal can be introduced into the body, with a coupling coil used to capture the signal externally For instance, in an implantable temperature detection device, a quartz crystal is embedded in the body to measure temperature, while an external magnetic coupling coil receives linear FM signals This method leverages the linear relationship between the crystal's resonance frequency and temperature, achieving measurement errors below 0.1 °C and demonstrating long-term stability.
Basics of Sensors and Measurement
Introduction
Biomedical sensing and measurement utilize advanced technologies and various sensors tailored to detect specific measurement objects The diversity of these sensors leads to different types, working principles, and structures, yet their evaluation methods remain largely consistent Key characteristics of sensors include "lifetime," which refers to sensitivity degradation in certain environments, and "repeatability," indicating uniform responses to identical inputs These features are categorized into static and dynamic characteristics, providing standardized evaluation criteria The essential properties of sensors, known as the "4s"—selectivity, sensitivity, stability, and safety—must be prioritized in both design and operation Sensor detection systems typically comprise sensors, measuring circuits, and output systems, with circuit designs varying based on measurement needs, such as parameter conversion and computation Measurement methods can be classified by the features of the measuring objects, including direct vs indirect, active vs passive, invasive vs non-invasive, and wired vs wireless approaches Notably, for implantable biomedical sensors in biological environments, ensuring compatibility with biological tissues is a critical challenge that also extends to in vitro sensor detection.
This chapter provides an overview of the essential components of biomedical sensors, including fundamental microfabrication technologies, key sensor characteristics, and measurement methods and systems Additionally, it highlights the significance of biocompatibility in the design of biomedical sensors due to its critical role in their effectiveness The subsequent chapters will build upon the foundational concepts and knowledge of biomedical sensors introduced here.
Sensor Characteristics and Terminology
The performance of a sensor is crucial as it impacts the overall measurement system Sensor characteristics are categorized into static and dynamic parameters, both of which are vital for understanding sensor behavior Static characteristics are assessed once transient effects have settled, while dynamic characteristics reflect the sensor's response to time-varying inputs, highlighting its transient properties.
Static characteristics are assessed under standard conditions, which include the absence of acceleration, vibration, or shock (unless shock is the subject of measurement) These conditions also specify a temperature range of 25±5 °C, relative humidity below 85%, and atmospheric pressure maintained at 101.3±8 kPa.
In standard static conditions, repeatedly measuring the sensor's output with high-accuracy instruments allows for the plotting of a static calibration curve based on the collected data This curve facilitates the determination of the sensor's static characteristics.
Because of the biomedical sensors’ special features, some static characteristics (such as lifetime, sensitivity, selectivity, etc.) are particularly important for them, and these characteristics are highlighted in this section
The lifetime of biomedical sensors refers to the duration they remain functional under standard operational conditions Since these sensors are often implanted in the human body, it is essential for them to endure the internal environment while consistently performing their intended functions.
Selectivity refers to a sensor's capability to detect a specific component while ignoring others, such as a calcium ion-selective microelectrode that remains unaffected by ions like Na+, K+, and Mg2+ Sensitivity, on the other hand, is defined as the ratio of the change in the sensor's output to the change in the input measurand For instance, if a gas sensor's output voltage rises by 1 V with a 1,000 ppm increase in oxygen concentration, its sensitivity is calculated at 1 mV/ppm This parameter is particularly crucial for biomedical sensors, where the signals are often weak, making sensitivity essential for accurately measuring electrophysiological signals.
A linear sensor maintains a constant sensitivity, whereas a nonlinear sensor exhibits sensitivity that varies with different inputs The static sensitivity of a sensor can be determined from its static calibration line, with linear sensors having a static sensitivity represented by the slope of this line.
Fig 2.1 Static sensitivity curves: (a) Linear sensor; (b) Nonlinear sensor
The detection limit refers to the smallest signal that can be identified within a sensing system, factoring in noise levels High noise relative to the input makes it challenging to discern a clear signal In the context of biomedical sensors, the human body’s complexity means that various signals interact, making it crucial to effectively extract target signals from a noisy background.
Apart from the points described above, there are also many other static characteristics extremely important for all sensors
Linearity refers to how closely a sensor's calibration curve aligns with a predetermined straight line, typically representing the sensor's theoretical behavior or its least-squares fit This concept is quantified as a percentage of the full-scale output (Y F.S.), indicating the maximum deviation (Δ max) of any calibration point from the corresponding point on the specified straight line, commonly denoted as ε.
Hysteresis refers to the maximum output difference, ΔH max, at any measured value within a specified range, observed when the value is approached first by increasing and then by decreasing measurements This phenomenon is expressed as a percentage of the full scale (Y F.S.) and can be calculated using the formula: max / F.S × 100%.
Repeatability is the sensor’s ability to produce the same response for successive measurements of the same input, when all operating and environmental conditions remain constant
Error refers to the discrepancy between a measured result and the true value, an occurrence that is unavoidable in any measurement process However, it is essential to minimize errors through advancements in techniques and concepts, as this enables a more accurate assessment of the validity of the results.
Accuracy refers to the degree to which a sensor's output aligns with the true value, and it is influenced by measurement bias This concept is quantified through absolute and relative errors, which can be calculated using the formula: absolute error = true value - measured value, and relative error = absolute error / true value.
In order to assess the accuracy of a sensor, either the measurement should be calibratedagainst a standard measurand or the output should be compared with a measurement system with a known accuracy (Wilson, 2005)
Precision refers to the number of decimal places in which a measurand can be reliably measured, highlighting the carefulness of the final reading rather than the measurement's accuracy It emphasizes the consistency between successive readings rather than their proximity to the true value.
Resolution refers to the smallest change in a measurand that can lead to a noticeable shift in the output signal, indicating the minimum input alteration required for a detectable output change.
Drift refers to the gradual and unintended change in a sensor's response while the measurand stays constant, often caused by factors such as aging, temperature fluctuations, contamination, and material degradation (Kalantar-zadeh and Fry, 2008) This undesired variation is unrelated to the actual input, making it a critical concern in sensor performance and accuracy.
Dynamic range, also known as span, refers to the spectrum of input signals that produce meaningful outputs from a sensor Each sensor is engineered to operate effectively within a defined range, and signals that fall outside this range can lead to significant inaccuracies or even damage to the sensor.
Sensor Measurement Technology
Sensor measurement technology is essential for signal detection and can be classified into various categories, including direct vs indirect, active vs passive, invasive vs non-invasive, and wired vs wireless methods A comprehensive sensor system must consist of a sensor interface, signal preprocessing circuits, and computer-aided Digital Signal Processing (DSP) hardware and software In challenging environments where signal detection is difficult, alternative methods may be employed to enhance the performance of the sensor system.
In this section we will introduce the following measurement methods: direct and indirect measurement, active and passive measurement, invasive and non-invasive measurement, and wired and wireless measurement
The direct measurement method involves obtaining results directly from instrument outputs, such as using an electromagnetic current meter to measure circuit currents and employing a bourdon tube pressure gauge to assess pressure levels.
The indirect measurement method relies on calculated results from measured parameters to determine final values, such as measuring inductance by analyzing the circuit's resonant frequency While this approach involves more steps and takes longer, it is typically employed only when direct measurement is impractical.
According to the power supply of the measurement system, measurement is divided into active measurement and passive measurement
The active measurement system, illustrated in Fig 2.7, is designed to provide power to the object being measured For instance, in impedance measurements, it is essential to apply an electrical voltage perturbation to the sample under test.
The structure of the passive measurement system is shown in Fig 2.8 The passive measurement system does not need power supplies from outside
2.3.1.3 Invasive and Non-invasive Measurement
Invasive measurement techniques can harm or alter the subjects being examined, while non-invasive methods exert minimal to no influence Various cancer detection methods exist, such as gene detection, blood tests, PET-CT scans, and the electronic nose (e-Nose) Notably, the electronic nose stands out as a non-invasive option, as it analyzes patients' exhaled breath without causing any harm, making it a significant advantage over other detection methods.
In recent years, wireless measurement technology has rapidly advanced, finding applications across various fields, including communication and biomedicine A notable example is the RFID-Based Closed-Loop Wireless Power Transmission System, which is particularly beneficial for powering implantable biomedical devices This system employs transmitter and receiver coils for wireless power transfer, where any variations in distance or alignment significantly affect the power received The closed-loop design allows for real-time detection of these changes, enhancing the ability to monitor implanted chips for disease detection (Mehdi and Maysam, 2010).
The advancement of micro-processing technology has significantly enhanced the composition of sensor detecting systems Modern sensor detection technology is increasingly focused on smart sensor systems equipped with microprocessors The fundamental components of these systems are illustrated in Fig 2.9.
Fig 2.9 Fundamental composition of a sensor detecting system
The detecting system consists of sensors, measuring circuits (including sensor interfaces and signal pre-processing circuits), and an output system Sensors act as primary instruments by detecting signals in the measurement environment and converting them into electrical signals The subsequent measuring and output circuits are classified as secondary instruments, playing a crucial role in the overall detection process.
Measuring circuits can be categorized into sensor interface circuits and pre-processing circuits The sensor interface circuit connects the sensor to the pre-processing circuits and typically includes parameter conversion, signal modulation, and impedance matching components to extract the measured signal Meanwhile, the pre-processing circuit encompasses operations such as demodulation, filtering, and both A/D and D/A conversions to detect and process the measured signal, including discrete signal processing when required Advanced intelligent sensing detection systems enhance this process by enabling self-diagnosis and self-recovery capabilities.
The measured signal alters the electrical parameters of sensors, including resistance, inductance, and capacitance These changes are typically transformed into voltage or frequency signals that are proportional to the original parameters, necessitating the use of parameter converting circuits (PCC).
Commonly utilized parametric conversion circuits encompass the bridge circuit, which converts resistance, inductance, or capacitance into voltage; the current-voltage (IV) conversion circuit; and the resistance, inductance, capacitance (RLC) oscillation circuit, which transforms resistors, inductors, and capacitors into voltage or frequency digital signals.
Sensors act as signal sources with specific output impedance, while the interface circuit has its own input impedance To minimize the impact of input impedance on the output signal, impedance transformation is essential in sensor interface circuit design Utilizing high input impedance amplifiers allows for the conversion of the sensor's high output impedance into a lower output impedance For instance, in the design of measuring circuits for piezoelectric sensors, voltage amplifiers play a crucial role in both impedance conversion and signal amplification.
Measurement circuits encompass various operation circuits, including ratio, addition and subtraction, integral, differential, logarithmic, exponential, and multiplication and division circuits Ratio computing is essential since sensor outputs are typically low, often at the millivolt level, necessitating amplification An integrated operational amplifier serves as an effective signal amplification device, categorized into non-inverting proportional circuits, which function as voltage amplifiers, and inverting proportional circuits, which act as current-voltage conversion amplifiers, based on their feedback connection methods.
Addition and subtraction circuits are essential for processing various signals and adjusting their amplitude bias A fundamental example of these circuits is the differential amplifier, which plays a crucial role in performing these operations effectively.
Logarithmic and exponential circuits: To achieve the non-linear operation in the circuits For example, logarithmic circuits can linearize the output of the exponential signals
In measurement systems, analog filters in the signal pre-processing circuit play a crucial role by selecting essential frequency components and effectively reducing noise These filtering circuits are designed to pass specific frequency ranges while significantly attenuating others Filters are typically classified into four categories based on their amplitude-frequency characteristics: low pass, high pass, band pass, and band stop Additionally, filters can be categorized based on their components.
Biocompatibility Design of Sensors
Biocompatibility is a crucial concept in biomaterial science, particularly for sensors utilized in biological detection and medical diagnostics Ensuring biocompatibility is essential to prevent hemo- or histo-compatibility issues arising from direct contact with biological tissues This section will explore the definition, classification, and evaluation of biocompatibility, highlighting its significance in sensor design The focus will be on two main types of sensors: invasive sensors for in vivo implantation and physiological monitoring, and non-invasive sensors for in vitro cell or tissue observation.
2.4.1 Concept and Principle of Biocompatibility
The following content will include the concept of biocompatibility, classification of biocompatibility and evaluation, which provide essential rules for biomedical sensor fabrication
Biomedical sensors, whether implanted in animals or humans or in direct contact with tissue in vitro, must be non-toxic, non-allergenic, non-irritating, non-genotoxic, and non-carcinogenic to avoid adverse reactions in tissues, blood, and immune systems Ensuring compatibility with the organism's chemical composition is crucial, making biocompatibility a top priority According to David (2008), understanding biocompatibility involves identifying the chemical, biochemical, physiological, and physical mechanisms that operate during the interaction between biomaterials and body tissues, as well as the consequences of these interactions Therefore, a thorough evaluation of both the responses of materials to human tissues and the specific natural processes in various applications is essential.
Biocompatibility poses significant challenges for biomedical sensors intended for clinical use, necessitating a comprehensive series of in vitro tests aligned with ISO 10993 standards to evaluate material compatibility These assessments are crucial for progressing to animal testing and ultimately clinical trials involving medical device implantation Given the complexity of the body's immune response and repair mechanisms, it is insufficient to assess the biocompatibility of a material based solely on its interaction with a single cell type or tissue Therefore, several key factors must be considered in the design of implantable biomedical sensors to ensure their effectiveness and safety.
Sensors are not supposed to be corroded or toxic In this way, they must be compatible with the chemical composition in organism
Sensors implanted in the human body must be designed to fit the anatomical structures of the areas they measure, ensuring that they do not cause any harm to surrounding tissues.
Sensors should be solid enough When implanted, the sensor should not be damaged
Electrical insulation is crucial for sensors to ensure safety when used in the human body In the event of sensor damage, it is essential to maintain the voltage applied to the human body below safe security levels to prevent harm.
Sensors should neither place physical activities a burden, nor interfere with the normal physiological function
The in vivo sensors used for long term implantation should not cause any vegetation
The structure of the sensor should be easily disinfected
Biomedical materials serve as crucial mediators between sensors and measuring objects, necessitating thorough investigation Table 2.1 outlines the primary interactions between these materials and the human body Both physical and chemical changes in the materials can lead to significant alterations in biological responses due to mechanical, physical, or chemical interactions While some changes are key factors influencing the host response, others play a vital role in the effective functioning of medical devices.
Table 2.1 The interaction between biological materials and the human body
Biomedical materials changes Response and changes in organisms
Allergic reactions, toxicity, hemolytic reaction, fever, paralysis
Size, shape, flexibility, rigid, plasticity, brittleness, relative density, melting point, conductivity, and thermal conductivity
Toxicity, teratogenesis, immune response, dysfunction
Hydrophilic, hydrophobic, pH value, adsorption, dissolution, permeability Chronic local reaction
Interaction between biomedical materials and organisms: (1) mechanical interaction: friction, impact, bending; (2) physical and chemical interaction: dissolution, absorption, permeability, degradation; (3) chemical interactions: decomposition, modification
Factors causing biomedical materials change:
The dynamic mechanics of bones, joints and muscles in physical activities; Cellular bioelectricity, magnetic fields, electrolysis and oxidation in cells;
Biochemistry and enzyme-catalyzed reaction in metabolic procedure; Adhesion and phagocytosis of cells;
Biodegradation by various enzymes, cytokines, proteins, amino acids, peptides, and free radicals in body fluids
Residual toxic low-molecular-weight substances in materials, irritating monomers from the polymerization process, and adsorbed chemical agents along with byproducts from high-temperature sterilization can pose significant health risks.
The shape, size, surface smooth level of the materials and products; The pH value of the materials
Biomedical sensors in the cardiovascular system must maintain compatibility with blood to function effectively Implanted devices should minimize adverse reactions to blood and tissue, as catheter insertion can lead to sensor failure from fiber accumulation and blood clots The presence of these devices can pose risks, including the release of toxic substances and increased thrombosis due to sensor charge or leakage currents Blood clotting time serves as a key indicator of material compatibility, with PTFE recognized for its superior inertness, exhibiting a clotting time of 11-13 minutes, compared to less compatible materials like inorganic silicon and glass, which typically have clotting times under 10 minutes Therefore, optimizing sensor design, catheter surfaces, and surface modifications is crucial in the development of invasive sensors.
Biomedical sensors implanted outside the cardiovascular system primarily examine the interaction between materials and biological tissues or organs Initially, the immune system produces antibodies against various antigens, including unfamiliar ones, but eventually ceases production for antigens already present in the body When exposed to foreign antigens, the immune system responds by attacking these external materials Consequently, it is crucial for the materials used in sensors to be histocompatible to prevent an immune response.
The safety of patients is directly linked to the quality and biocompatibility of biomedical materials and medical equipment, necessitating a standardized registration and approval process, such as ISO 10993 To ensure safety, biomaterials and medical devices must undergo biological evaluations during research and manufacturing Biomedical materials safety encompasses four key aspects: physical properties, chemical properties, biological properties, and clinical research, with a focused evaluation on the biological assessment of biomaterials and medical devices.
Biological assessment generally contains the following aspects:
Contact tissues: body surface and body tissues, bones, teeth, blood; Contact means: direct contact and indirect contact;
Contact time: Temporary contact is less than 24 h, short and medium- term exposure is longer than 24 h but shorter than 30 d, and long-term exposure is more than 30 d;
Purpose: general function, reproductive and embryonic development, biodegradation
Silk fibroin materials, utilized in the construction of artificial nerve grafts, have been biocompatibility evaluated with tissues and cells (Yang et al., 2007) The study included a comprehensive physical and biological characterization of these materials, along with a biological assessment involving direct contact with cells Observations of rat dorsal root ganglia cell outgrowth were conducted using light and electron microscopy, supplemented by immunocytochemistry Additionally, the morphology and proliferation of Schwann cells were assessed through MTT tests and cell cycle analysis.
2.4.2 Biocompatibility for Implantable Biomedical Sensors
State-of-the-art implantable biomedical sensors are classified into biophysical sensors for bioelectric detection and biochemical sensors for metabolite detection These advanced sensors include devices that detect electrical signals in the brain and monitor bio-analytes, providing critical insights into neurological functions and metabolic processes.
To minimize chemical reactions in metallic systems, stainless steels have replaced corrosive plain carbon and vanadium steels, followed by highly passivated cobalt-chromium alloys, titanium alloys, and platinum group metals In cardiac pacemakers and implantable cardioverter defibrillators, which are essential for managing various cardiac rhythm disorders, active components are encased in sealed titanium cans Leads transmit pulses for sensing and delivery from the can to the electrode placed on the heart The electrode must prioritize high electrical conductivity, as well as fatigue and corrosion resistance, utilizing alloys such as platinum group metals or cobalt-chromium alloys.
The introduction of advanced polymers has led to the replacement of traditional nylons and polyesters with more degradation-resistant materials like PTFE, PMMA, polyethylene, and silicones The emergence of degradable implantable materials enhances the concept of biocompatibility, allowing these materials to perform their functions while ensuring an acceptable host response Notably, drug delivery systems utilize degradable polymers such as polylactide and polyglycolides, as well as poly(methylidene malonate), to create effective microspheres.
The design of biocompatible biomedical sensors for in vivo applications presents challenges related to surface materials, device morphology, infection risks, toxicological effects, and host responses (Reach et al., 1994) A chemically modified working electrode must feature a compatible surface that allows for the selective permeation of target solutes while rejecting interfering substances The outer membrane's structure and properties, which directly contact host tissue or blood, are crucial for ensuring high transport selectivity and preventing the leakage of toxic components Additionally, the morphological characteristics impact the sensor's sensitivity; any mechanical damage or detachment from the enzyme layer can lead to abnormal sensor function Addressing bacterial adherence and host toxicity is essential for successful sensor deployment Recent advancements include catheter-type sensors for blood-gas measurements, such as pH and P O2, which are increasingly being replaced by non-invasive pulse oximeters (Collison and Meyerhoff, 1990) Furthermore, needle-type glucose sensors utilize multiple membrane coatings and electrodeposition of glucose oxidase (Robert et al., 1989), while ion-selective electrodes and field-effect transistors have been developed for monitoring electrolytes like Na+, K+, and Ca2+ (Kimura, 2001).
How to evaluate the biocompatibility of the sensor? Yang et al (2003) developed an optic micropressure sensor and evaluated its biocompatibility using the International Organization for Standardization (ISO) test standard 10993-6,
Microfabrication of Biomedical Sensors
Biomedical sensors must be compatible with biological components and minimize invasive injury during in-vivo measurements The advancement of microfabrication technology enhances the potential of these sensors, offering benefits such as low cost, reduced sample consumption, high-throughput performance, and easy integration into systems This section introduces fundamental microfabrication techniques, including lithography, film forming, and etching, and illustrates a typical sensor fabrication procedure.
Lithography in MEMS involves transferring a pattern onto photosensitive material, which is crucial for sensor fabrication The process of applying the designed image onto a resist-coated wafer is essential The two primary lithography techniques utilized in sensor fabrication are photolithography and electron beam lithography.
Photolithography is the leading technique in lithography, utilizing a photo mask, typically a flat glass or quartz plate with a metal absorber pattern This mask is placed in direct contact with a photoresist-coated surface, allowing ultraviolet radiation exposure to transfer the pattern based on the photoresist's polarity The technology has advanced significantly, achieving higher resolution for smaller features, making it ideal for fabricating micro sensors in dimensions of several microns.
Electron beam lithography (EBL) surpasses the resolution limits of photolithography by utilizing the exceptionally small wavelengths of high-energy electrons, eliminating the need for a photo mask and allowing for direct writing on resist-coated surfaces Its key advantages include precise registration over small wafer areas, reduced defect densities, and a large depth of focus due to continuous topographical focusing However, EBL faces challenges such as rapid electron scattering in solids, which restricts practical resolution to above 10 nm, and exposure variations in micrometer and sub-micrometer patterns Additionally, the requirement for a vacuum complicates the apparatus, increasing costs compared to photolithography The relatively slow exposure speed and high system costs further limit the widespread adoption of scanning electron-beam lithography.
The film formation process in microfabrication involves the growth and deposition of layers using various materials Key techniques for creating films include silicon oxidation, physical vapor deposition (PVD), and chemical vapor deposition (CVD), each playing a crucial role in the development of diverse material films.
Silicon oxidation is a crucial step in sensor fabrication, as silicon serves as the primary base material The process involves heating a silicon wafer in a steam environment or a mixture of wet or dry oxygen and nitrogen at elevated temperatures ranging from 600 to 1,250 °C This high-temperature environment facilitates the diffusion of oxidants through the surface oxide layer to the silicon interface, enabling the rapid formation of thick silicon dioxide layers This technique is essential in the production of various silicon-based sensors, including light addressable potentiometric sensors (LAPS).
2009), silicon oxidation is usually a necessary procedure
Gas phase deposition is a key technology in film formation Two major categories of gas phase deposition can be distinguished as PVD and CVD
Physical vapor deposition (PVD) is a line-of-sight deposition method that utilizes solid, liquid, or vapor raw materials in various configurations The two primary techniques for PVD are evaporation and sputtering Thermal evaporation, one of the oldest thin film deposition methods, involves heating materials in a vacuum, but can lead to shadowing issues on small structures In contrast, sputtering uses a negatively charged target bombarded by positive argon ions in a plasma, offering advantages such as a broader material selection, improved step coverage, and enhanced adhesion to substrates While sputtering is commonly used in both laboratories and production environments, evaporation is primarily limited to laboratory applications.
Chemical vapor deposition (CVD) is a mass transfer technique that operates through diffusive and convective processes, with various methods available that differ in operational pressures and temperatures Plasma-enhanced chemical vapor deposition (PECVD) utilizes RF-induced plasma to energize reactant gases, enabling lower substrate temperatures and compatibility with existing dry etching equipment PECVD is particularly notable for its application in depositing SiO2 or Si3N4 over metal lines In contrast, low pressure CVD (LPCVD) operates below 10 Pa, allowing for the simultaneous coating of multiple wafers while maintaining film uniformity, though it is limited by a lower deposition rate and higher operating temperatures.
Screen printing plays a crucial role in the cost-effective fabrication of disposable sensors, which are increasingly significant in biosensor applications This process involves pressing an ink paste—composed of the desired material, an organic binder, and a solvent—onto a substrate through openings in a stainless steel screen's emulsion The lithographic pattern is created by using a squeegee to force the paste through the mask openings Initially, paste is applied to the screen, and as the squeegee moves horizontally, it presses the screen onto the substrate, allowing the paste to pass through the openings Finally, the screen snaps back, shearing the thick-film paste and forming the printed pattern on the substrate The resolution of this screen printing technique is influenced by the size of the openings and the characteristics of the pastes used.
Etching is a crucial process in wafer fabrication that removes material from unprotected areas to create functional structures Typically following lithography, etching ensures precise pattern alignment with the photomask In MEMS fabrication, the two primary types of etching are wet etching and dry etching.
Wet etching is a chemical process that selectively dissolves films using an etchant, involving three main steps: the diffusion of reactive species from the liquid to the film's surface, the reaction at the surface forming soluble species, and the diffusion of reaction products back to the liquid The etch rate is influenced by temperature, specific reactions, and liquid concentration, leading to isotropic etching, where etching occurs uniformly in all directions, and anisotropic etching, characterized by varying etch rates in different directions, particularly in crystalline materials like silicon Wet etching typically achieves good selectivity, as the etch rate of the target material is significantly higher than that of the mask material.
Anisotropic etching on a silicon wafer results in a cavity with plane sides, forming a distinct angle of 54.7 degrees, while isotropic etching maintains a uniform etch rate across all directions.
Dry etching is preferred for its precise control over the etching process and its safety advantages, as it avoids the use of hazardous acids and solvents found in wet etching This technique efficiently etches specific films through three main methods: chemical reactions with reactive gases or plasma, physical bombardment of atoms, and a combination of both chemical and physical removal processes.
Plasma etching is a chemical dry etching technique that utilizes RF excitations to ionize gas and create reactive species that interact with the wafer's surface This process involves adsorption and chemical reactions, leading to the desorption of byproducts into the gas In contrast, sputtering is a physical dry etching method that removes material by bombarding it with energetic, inert ions, making it non-selective and potentially damaging to the mask layer Consequently, sputtering has not gained popularity in MEMS fabrication compared to chemical methods.
Reactive ion etching (RIE) is a crucial technique in semiconductor fabrication, merging chemical and physical processes to effectively etch targeted materials using accelerated reactive ions Unlike plasma etching, RIE offers enhanced anisotropy and improved directional movement due to the electric field Its etch rate is highly controllable, providing reasonable material selectivity and optical endpoint detection RIE can achieve significant etch depths, particularly through its deep RIE subclass, which utilizes the Bosch process with alternating gas compositions to create nearly vertical sidewalls This capability makes RIE essential for forming intricate patterns in biochips and MEMS development, as illustrated by an example from SINTEF.
Fig 2.16 DRIE for through wafer holes: Average etch rate was 12 àm/min and each hole was
400 àm deep with diameter of 50 àm holes
2.5.4 Design of the Biomedical Sensors