Non destructive Detection of Electrocardiogram based on Microelectronics and Raman
Spectroscopy Technology
MaLeping
Copyright © The Institute of Electronics and Information Engineers(IEIE)
Keywords
Medical intelligent sensors, Raman spectroscopy, Non destructive testing, Medical field, Laser ultrasonic testing
1. Introduction
Sensors can convert various external data parameters such as physics, chemistry, and
mechanics into certain expressions, making them an important tool for information
transmission and acquisition [1]. Most medical testing instruments are centered around various sensors. Considering
the particularity of medical examinations, medical sensors need to have higher accuracy,
reliability, and anti-interference capabilities. At the same time, they also have
high requirements in various characteristics such as volume, weight, quality, and
service life [2]. With the rapid development of information technology, Internet of Things technology,
and sensor technology, medical sensors have made revolutionary progress. Intelligent
sensors have not only undergone changes in external devices in the medical field,
but also have new research results in their internal definitions [3]. The increasing demand for medical sensors has become an important constraint on
the development of medical sensors. How to fully save, output, and store the transmitted
data during patient testing is an important direction for the development of medical
intelligent sensors [4]. The functions of intelligent sensors need to include self compensation and self
diagnosis. Through microprocessor algorithms, the output status of the sensor can
be checked and the diagnostic results can be directly presented. The information storage
and memory functions are also important ways for doctors to query historical data
and necessary parameters. In addition, self-learning and adaptive functions can be
achieved through microprocessors embedded with advanced programming capabilities [5]. In the work process, according to certain behavioral criteria, component parameter
sequences are adapted to the medical detection process, providing assistance for the
accuracy of medical detection results [6].
From this, it can be seen that medical sensors are an important branch in the biomedical
field and one of the core components of various medical devices, which can represent
the process and effectiveness of the current high-level development of medical equipment
[7]. With the continuous improvement of intelligent sensor technology, medical intelligent
sensors have entered a new stage of rapid development, and have also made certain
innovative breakthroughs in this field. Medical intelligent sensors can replace and
extend, enhancing the sensory organs of doctors during the diagnostic process [8]. With the rapid development of microelectronics, wireless sensing technology, new
nanomaterials, and non-destructive testing technology, the field of medical sensors
has faced new challenges and opportunities. More and more researchers are paying attention
to more sensitive, precise, and responsive medical sensor devices [9]. In practical medical testing, the loss of data transmission can easily reduce the
accuracy of detection results. Due to the high quality requirements of medical detection
data, conventional detection parameters and methods are difficult to meet the needs
of intelligent sensors. Therefore, the combination of non-destructive testing technology
and intelligent medical sensors is becoming increasingly widespread. It can use advanced
technology and testing methods to develop testing results towards higher accuracy,
intelligence, and informatization without damaging the testing results. At present,
non-destructive testing technology has been widely applied in various fields such
as aviation, transportation, industry, and medicine [10]. In our research on the optimization of non-destructive testing technology for medical
intelligent sensors, we should focus more on exploring the development and current
status of non-destructive testing technology, selecting suitable methods from various
testing methods in the medical field, and improving the reliability of testing results.
2. Development Status of Non-destructive Testing Technology in Various Countries
With the progress of science, technology, and society, modern medicine has increasingly
high requirements for data management methods and detection results. People have found
that in the conventional detection process, parameter results and detection instruments
are no longer able to meet the needs of modern technology, from ordinary single parameter
data to multi parameter dynamic data [11]. When using automatic detection technology for data state estimation, it is difficult
to determine whether the accuracy of the detection data can be above the standard
coefficient [12]. This situation has become an important obstacle in the current development process
of the detection field. The current detection technology has higher requirements for
damage rate, and non-destructive effects have also achieved certain results in various
fields [13]. It can use physical or chemical methods, combined with advanced technological equipment,
to analyze the internal structure, surface composition, and characteristic state of
the tested object without compromising the data results. So, non-destructive testing
technology is developing towards intelligence, low radiation, informatization, and
diversification [14]. Domestic scholars have applied non-destructive testing technology in industries
such as industry and power, achieving resource sharing and data complementarity, enabling
the comprehensive and coordinated development of the industrial industry. This not
only promotes technological progress, but also increases economic benefits.
At present, there are many styles of non-destructive testing methods, and the use
of feedback data from ultrasonic and radiographic testing has certain reference value
in various fields [15]. Foreign researchers have applied these technologies in food safety and non-destructive
testing of product quality, while also playing a huge role in the medical industry.
Japanese scholars have found that non-destructive testing technology can assist in
medical diagnosis, such as improving the imaging effect of medical images in X-ray
fluoroscopy [16]. The improved accuracy of data results such as CT, MRI, and ultrasound can also assist
in the treatment of certain diseases, such as radiotherapy and chemotherapy, which
have certain advantages. Radiographic non-destructive testing refers to the complex
interaction between radiation and the internal structure of the object being tested
when it passes through it. Attenuate the transmission intensity, contrast the defect
area with the non defect area, and detect the internal problems of the object by analyzing
the radiation intensity. Reuse its wavelength change and energy consumption to achieve
the effect of photoelectric detection. This non-destructive testing technology can
not only visually determine the size and location of internal defects, but also determine
the specific positioning range, thereby helping doctors quickly determine the location
of the disease and carry out targeted treatment [17]. However, long-term experiments by foreign researchers have shown that excessive
radiation non-destructive testing can lead to a decrease in the patient's immune system
and trigger other diseases. Therefore, non-destructive testing technology has been
continuously optimized and improved in the medical field. American researchers have
found that ultrasonic non-destructive testing, which uses ultrasound to examine the
tested object and then displays it with ultrasound testing instruments, can achieve
certain results and improve the defects of radiographic non-destructive testing [18]. By using high-frequency ultrasound to reflect in different heterogeneous interfaces,
the reflection results are fed back to the doctor. In other words, when encountering
internal defect problems, some of the reflected energy returns to the sensor medium
along the pathway. Sensors output electrochemical signals in another way, providing
the displayed results directly to doctors for reference. Ultrasonic waves propagate
in the tested object, and due to changes in acoustic characteristics and internal
organization, phenomena such as reflection and transmission occur [19,20]. The accuracy of its research results will also be affected to varying degrees, so
more exploration and innovation are needed to optimize the non-destructive testing
process of medical intelligent sensor technology.
3. Research on Non-destructive Testing Technology based on Medical Intelligent Sensor
Technology
3.1 Medical Intelligent Microsensor Technology
The concept of intelligent sensors was first proposed in the aviation industry in
the United States and was developed into a product in the 1970s. They refer to the
integrated sensor that provides control or sensing data to be tested as an intelligent
sensor, and believe that this sensor device carries a microprocessor and has various
functions such as information detection, memory, storage, and logical judgment. Until
now, it has been widely believed that intelligent sensor technology can automatically
collect information from the external environment, and can process and judge data,
with certain self diagnosis and adaptive capabilities. Medical intelligent sensor
technology mainly consists of sensor microprocessors, input/output circuits, and various
data software. Its structure is shown in Fig. 1:
From Fig. 1, it can be seen that the sensor is divided into two parts: pre-processing and post-processing.
The data is transmitted into the sensor according to the tested object, and then the
sensor equipment processes the signal, converting it into a circuit or other representation.
After connecting to the output interface, the data output is displayed. In addition,
the sensor also needs to be connected to the software part to prepare for data input
and perform preprocessing adjustments, selection, etc. The concept of medical intelligent
sensors has greatly extended compared to traditional ordinary sensors. It fully utilizes
the computing and storage capabilities of computers, which can make the data information
collected during the testing process more complete. Traditional sensors are only a
component of intelligent sensors, which only perform the function of obtaining data
from the tested object and have no other characteristics. Medical intelligent sensor
technology converts physical quantities during the testing process into corresponding
electrical signals, which are then transmitted to signal processing circuits. The
signals are filtered, amplified, and analog-to-digital converted before being added
to computer microprocessing calculations. This micro sensor technology is also a core
component of intelligent sensors, which not only manages and stores data, but also
adjusts the medical detection process through feedback loops. We compared and explored
the frequency changes of medical intelligent sensor technology research in different
countries in recent years through literature review data:
Fig. 1. Structural diagram of medical intelligent sensors.
Fig. 2. Research frequency of medical intelligent sensor technology in different countries.
From Fig. 2, it can be seen that developed countries such as the United States and Japan started
researching medical intelligent sensor technology earlier, and there have been relatively
many related literature studies [21]. With the rapid development of electronic technology, computer technology, and sensor
technology in recent years, research on medical intelligent sensor technology has
become increasingly mature. At the same time, the increasing popularity of portable
intelligent wearable devices worldwide has also brought about significant changes
in medical sensor technology. Traditional sensors are relatively weak in terms of
extensibility, comfort, and adaptability based on metal and semiconductor materials.
In the later stage, the advantages of high convenience, high sensitivity, and high
response speed brought by micro sensor technology have become a hot research topic
in the medical field. In terms of blood oxygen detection, invasive testing brings
increasingly serious trauma to patients, and the operation is complex and difficult
to achieve real-time monitoring. Now it has gradually been replaced by non-invasive
testing. Checking the patient's blood oxygen saturation and total hemoglobin is the
main physiological parameter for judging whether the human respiration is normal,
and its expression formula is as follows:
With the increasing demand for accuracy and efficiency in blood oxygen detection in
medical clinical practice, the use of non-destructive testing technology to improve
the detection effect of medical intelligent sensors has become the main development
trend. The main structure of the sensor equipment with micro computing elements added
in our experiment is composed of a red ray and near-infrared printed sensor array.
Place a photodiode array at the top of the device to display waveform data. The working
principle is to use the difference in molar extinction coefficient between spectra
for comparison and measurement, and to improve the propagation effect of Beer's law
in blood oxygen measurement by combining red light with any other two combinations.
The expression is as follows:
In the formula $Y(\lambda )$ as the reflection intensity coefficient received by the
sensor,$I_{0}$ for the intensity of input light,$\mu $ is the absorption coefficient.
The expression result represents the difference between the light absorbed and reflected
by the miniature medical intelligent sensor during operation. The research in this
article mainly focuses on the automatic perception of patient sign data and health
index by medical intelligent sensors in the design. Monitor human electrocardiogram,
body temperature, body posture, and other processes, and transmit these perception
information to intelligent terminals through wireless transmission. After data collection
and analysis, upload it to the hospital database through the internet.
3.2 Research on Raman Spectroscopy Non-destructive Testing based on Medical Intelligent
Sensor Technology
After literature review, it was found that non-destructive testing technology has
many applications in the medical field. Traditional radiographic testing methods only
rely on the complex interaction between radiation and material atoms, and determine
the defect location by judging the degree of attenuation of radiation intensity. This
method can not only perform medical diagnosis, but also carry information on the distribution
of various human densities, and receive data through sensors for display and pathological
diagnosis. In addition, X-ray non-destructive testing also has good effects in treatment,
judging changes in human cell and tissue based on biological effects, causing damage
or inhibition of irradiated cell and tissue, thereby achieving disease control. On
the other hand, it causes significant damage to the normal body of the human body
and is not suitable for multiple examinations and treatments in a short period of
time. CT scanning is a non-destructive testing method optimized based on radiographic
testing technology. After converting the radiation into visible light, it undergoes
digital to analog conversion through electrical signals, and finally inputs it into
a computer for processing, displaying human body information on the image screen.
It commonly uses cross-sectional images to reflect the degree of radiation absorption
by organs and tissues in different grayscales. Due to the high resolution of CT detection
and the ability to produce specific imaging data, it is currently widely used in clinical
practice. However, this detection method is expensive and the equipment is also quite
expensive, so it also has certain limitations and should not be used as a routine
diagnostic method. Ultrasound non-destructive testing technology has also gained a
wide coverage in medical applications, known as ultrasound diagnostics. Observe the
reflection of ultrasound by the human body, and finally perform image processing to
understand the internal situation of the tested object. It has low intensity and high
frequency, and although it does not cause significant damage to the human body, there
is a certain feedback delay. We compared the superiority of the three non-destructive
testing techniques mentioned above in medicine, as shown in Fig. 3:
Fig. 3. Comparison of the advantages and disadvantages of three non-destructive testing techniques.
From Fig. 3, it can be seen that the ultrasound diagnostic method has high superiority, and its
principle is to use pulse echo to complete the imaging process. After the human body
emits a set of ultrasound waves, it scans in a certain direction [22]. However, during the experiment, we also found that the delay of ultrasound non-destructive
testing has a significant obstacle for doctors to judge the actual situation of patients.
Raman spectroscopy non-destructive testing technology, as a comprehensive technology
developed on the basis of modern computer, electronics, and sensor technology, can
provide fast, simple, and repeatable non-destructive quantitative analysis. This method
has a higher transmittance and a clearer and sharper peak in data response, making
it more suitable for medical use. We will use Raman spectroscopy technology to perform
diffusion testing on cancer patients in subsequent experimental tests. When the ion
motion direction in the spectrum exhibits an axisymmetric mode propagation pattern,
the change in spectral frequency also changes accordingly. The relative velocity and
detection point group velocity are important concepts in propagation data, and the
formula is as follows:
In the formula $C_{p}$ as a relative wavelength velocity, the population velocity
of the test point has a certain characteristic, such as the expression relationship
between the energy propagation of the wave group and the relative velocity at the
maximum peak value, as follows:
Our most intuitive consideration for explaining the concept of spectral data transmission
speed is that the frequency varies under different amplitudes.
Fig. 4. Changes in absorbance wavelength and resonance peaks in Raman spectroscopy.
As shown in Fig. 4, the measurement results of spectral data provide important basis for the key parameters
of Raman spectroscopy imaging detection sensing devices. In general, Raman spectroscopy
uses visible light as the excitation source to improve the spectral signal efficiency.
The position of the characteristic peak spectrum also shows the distribution range
of diseased cells in cancer patients, which cannot be provided by conventional spectral
detection methods.
After overlapping two sets of harmonic spectra, form a combination formula:
Wherein $A$ for amplitude,$k_{1}$,$k_{2}$ represent two wave values with different
values. According to the sum difference product formula, the function value of the
measured data can be combined with the sum difference result to obtain the following
formula:
Transform all the above formula functions:
The transformed formulas are combined into the following expression:
The low-frequency and high-frequency propagation data of Raman spectroscopy can be
processed by binarization threshold after being collected through imaging technology
to obtain corresponding images.
4. Analysis of Research Results on Non-destructive Testing Technology based on Medical
Intelligent Sensor Technology
4.1 Results Analysis
With the increasing challenges faced by the medical field in the development of new
technologies, sensor research based on the medical Internet of Things has become a
core part of intelligent vital sign monitoring and medical detection. Medical intelligent
sensors use the method of wireless transmission of data information to divide the
vital feature data of the monitored object in the perception layer, effectively collecting
characteristic information such as body temperature, posture, electrocardiogram and
blood pressure. When a patient experiences abnormal detection conditions, an alarm
is issued through the intelligent monitoring system, and positioning marks are made
during the detection, allowing medical staff to analyze and treat the pathology in
the shortest possible time. We mainly combine embedded micro sensor components in
our research to optimize medical intelligent sensor devices into more precise and
compact forms. By combining various functions such as self compensation, self calibration,
and self diagnostic data processing, it can ensure a certain level of transmission
accuracy and reliability when facing large amounts of data transmission and real-time
requirements.
As shown in Fig. 5, the sensor is mainly composed of various components such as microprocessors, power
supplies, detection systems, indicator guidance, and wireless communication. The wireless
sensor in Fig. 5 does not use I2C bus for communication, but instead uses wireless communication technology.
This design enables sensors to be more easily deployed in the required locations without
considering the complexity of wiring, while also improving the flexibility and scalability
of the system. Adopting a micro structure design and exquisite appearance, the power
supply is combined with a single pressure switch charging method, and energy-saving
light sources are used for indirect lighting reminders. In addition, sensors can also
transmit data over a certain communication distance, with a transmission speed of
over 1Mbps. Up to 12 smart terminals can be logged in, and if no connection is established
within one minute, it will enter sleep mode. When conducting non-destructive testing
on patients, in addition to analyzing data on electrocardiogram, body temperature,
and posture, those data can also be sampled and stored in a per second format. The
internal temperature sensing has high accuracy and sensitivity, and can sense temperatures
from -10 $^{\circ}$C to 57 $^{\circ}$C. Combined with an electrocardiogram perception
simulator, it is displayed on an integrated screen using digital data processing,
analog-to-digital conversion, and other methods. In the above study, we mainly compared
the results of the patient's blood oxygen content test with the optimized medical
intelligent sensor technology's molar extinction coefficient, and displayed the data
as follows:
Fig. 5. Principles of Medical Intelligent Microsensors.
Fig. 6. Change in molar extinction coefficient.
As shown in Fig. 6, we represent the different components of blood oxygen content with three different
types of light. Green light represents the wavelength of blood oxygen content in the
patient's body, red light represents the reflection wavelength of hemoglobin inside
the blood, and orange represents the reflection wavelength of blood cells. Through
the comparison of non-destructive data before and after, it was found that the medical
intelligent micro sensor technology used in this experiment has a relatively small
amount of data damage and can basically reach a non-destructive state. On the left
or top of Fig. 6, label one or more light source points that emit specific wavelengths of light (such
as green, red, and orange light) corresponding to the detection of blood oxygen content,
hemoglobin, and blood cells, respectively. The light source should include LED lights
or laser sources with tunable or fixed wavelengths, which can accurately control the
wavelength of the emitted light to meet the detection needs of different components.
The sample should be placed in a transparent or semi transparent container so that
light can penetrate and interact with it. The sample can be an actual patient blood
sample or simulated tissue.
4.2 Comparison of Application Results
The research objects of biomedical science are biology and humans, and the unique
characteristics of the human body often require measurement of different organs and
data in medicine to obtain reliable analysis. The different parameters of various
organs can easily have various impacts on the detection method during the detection
process, so the detection data needs to have high anti-interference ability to meet
the needs of medical equipment. Based on these current situations, medical intelligent
sensors are more inclined towards large-scale integrated environments, combining the
different functions of multiple chips to achieve the transmission and monitoring of
various human data. Further improve the miniaturization of medical intelligent sensing
equipment, combining computer, electronic, wireless and other technologies. Medical
instruments achieve wearable, implantable, and intelligent sensor monitoring. In addition,
the input and output methods faced by intelligent sensor technology in practical applications
can also cause data damage, while being limited by distance and other factors. Therefore,
in the optimization of medical intelligent sensors, this article adds networked service
functions to the input and output links, protecting the transmission integrity of
underlying data through the connection of multiple nodes. In the above experiment,
we used Raman spectroscopy technology to perform non-destructive testing on patients,
restoring the cellular changes and spectral wavelength peak localization in the patient's
body. In addition to being able to reflect in patients with hematological diseases,
it also provides effective assistance for pathological analysis of cancer patients.
This comprehensive absorption spectrum can clearly distinguish the spectral differences
between health and disease. Therefore, we use discrete data graphs to demonstrate
the comparison of Raman spectroscopy detection for two types of health and disease:
On the left or top of Fig. 7, label a laser light source, which is a key component for Raman spectroscopy measurement.
Laser light sources emit laser beams with good monochromaticity, strong directionality,
and high brightness. Usually, near-infrared or visible light wavelengths are selected
to avoid damage to biological tissues. The wavelength of the laser should be selected
based on the characteristics of the sample being tested to excite the required Raman
scattering. The sample stage should be designed to be stable and adjustable for precise
control of the interaction position between the sample and the laser beam. For biological
samples, it may be necessary to maintain certain temperature and humidity conditions.
As shown in Fig. 7, the internal absorption spectrum of healthy individuals is relatively complete,
while there are obvious defects in the internal absorption spectrum of diseased individuals.
The experimental operation is simple, and in practical applications, results can be
obtained within 10 minutes. This technology causes minimal internal damage to the
human body and has a lower data loss rate during transmission, truly achieving lossless
data transmission. It can help the medical field further achieve results in cell surface
analysis and blood research. In addition, the non-destructive testing effect achieved
by Raman spectroscopy technology can also directly affect human and biological skin,
muscles, organs, soft tissues, and other parts. By analyzing the strong light scattering
and absorption spectra of the cortex, a complete spectral imaging image can be obtained.
When biological or human tissues undergo lesions, the spectral imaging shows defects
and provides effective information for doctors. The tools used for non-destructive
testing under this medical intelligent sensor technology are also relatively simple
and can meet the common needs of major hospitals. In addition to using a standard
short arc lamp source as the light source, controlling the monochromator, scanning
instrument, and amplification instrument can form a reference image of spectral absorption
in the sensor photoacoustic cell. From this, it can be seen that non-destructive testing
technology has truly helped medical intelligent sensor technology to achieve a leapfrog
development.
Fig. 7. Raman spectroscopy discrete plot.
5. Conclusions
With the rapid development of emerging technologies such as microelectronics, wireless
electronics, and sensors, conventional detection methods and instruments are no longer
able to meet the needs of the medical field under modern progress. Non destructive
testing technology has become the main means of capturing and inspecting the internal
state and data of the tested object using more advanced methods without damaging data.
This non-destructive testing optimized medical intelligent sensor has the characteristics
of small size, low power consumption, high sensing sensitivity, low cost, and strong
detection speed and reliability. We analyze the research on non-destructive testing
of medical intelligent sensor technology based on this development status. Firstly,
we investigate and elaborate on the promotion of medical intelligent sensor technology
in the medical field. Due to the complex internal structure and strong exclusivity
of the human body, many detection methods are prone to potential harm to the human
body. How to optimize medical intelligent sensor technology has become the focus of
our research. This article also combines micro high-speed data acquisition sensing
elements to simplify the composition and structure of traditional sensor devices,
and improves the stability of performance without affecting data transmission and
work efficiency. Secondly, through the analysis of Raman spectroscopy non-destructive
testing technology, the non-destructive testing images of human blood and cancer pathology
analysis were determined. Use photometry to obtain the absorption wavelength change
curve and mark the range of resonance spectrum peak position. Finally, using Raman
spectroscopy non-destructive testing technology, the internal detection data of healthy
and diseased human bodies were collected, and the experimental results were judged
based on spectral imaging images. The research results indicate that the research
on non-destructive testing technology based on medical intelligent sensor technology
can provide reliable basis for doctors to judge data information, and has certain
medical and economic value.
Funding
This work was supported by the Shanxi Pharmaceutical Vocational College Foundation(2023222).
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Leping Ma was born in Wenshui, Shanxi, China, in 1984. She is currently a lecturer
in the Department of Medical Devices at Shanxi Pharmaceutical Vocational College.
For many years, she has mainly been engaged in the maintenance and management of medical
devices, as well as the teaching management of pharmaceutical equipment application
technology. She has made outstanding contributions in professional construction, training
room construction, skill guidance, and school enterprise cooperation. Her main research
direction is Signal detection and processing.