Biophotonic technology utilizes the properties of light, such as reflection, refraction, scattering, and absorption, to measure physical or chemical parameters in biological tissues. These parameters help to understand the structure, function, and metabolism of biological tissues, such as oxygen saturation, pulse rate, and respiration rate. The application of biophotonics in wearable devices offers the advantages of non-invasiveness, high sensitivity, and multi-functionality, making it a promising technology. Additionally, it can be integrated with other sensing technologies to enable physiological signal monitoring and health management.
Because skin tissues react differently to various light wavelengths, such as the formation of penetration, reflection, diffusion, and absorption of biophotonic behavior. In the simulation of different wavelengths of light irradiation on skin tissues, through the analysis of their light energy changes and light distribution, we can understand the response of skin tissues to light (e.g., melanin absorption, PPG status) to achieve the goals of non-invasive optical R&D and the optimization of components or preliminary system design.
Image source: kknews, health
The principle of achieving this optical simulation analysis is that when a light source irradiates the skin surface, each heartbeat causes the blood vessels to contract and expand, which in turn causes changes in the diffusion and absorption of light. When the light wave passes through the skin tissue and returns to the photodetector, the light energy attenuates to a certain extent, which helps in analyzing the state of PPG. Many physiological signals are analyzed through the PPG signal, such as pulse rate, blood oxygen saturation, and respiration rate.
By the absorption characteristics of different light wavelengths in blood, important physiological parameters can be analyzed. For instance, the different absorption coefficients of oxygenated hemoglobin (HbO2) and hemoglobin (Hb) at different wavelengths of light can be analyzed to determine the degree of blood oxygen saturation (SpO2). Other parameters, such as blood glucose and skin moisture content, can also be simulated and analyzed using this principle.
In accordance with the tissue differences in different parts of the organism, device structural appearance, and sensor specifications, we simulate and construct the optical sensor system that matches the skin. Before actually manufacturing the hardware, analyze the efficiency of optical measurement and S/N ratio, optimizing the quality of the optical signal.
Contactless biophotonics technology is most commonly used in the design of optical systems for eyes. By utilizing the different light absorption rates of various tissues of the eye, tBPC analyzes the structure of the eyes and selects the most suitable wavelengths for the purpose of measurement and analysis in optical design. It can also simulate and construct eye-related diseases, such as nearsightedness, farsightedness, and cataracts, to understand the differences in the optical system.
Image source: Laser safety Outline: Laser effects on tissues (skin and eyes)
The simulated light source is used to irradiate biological tissues and analyze the effects of wavelength and energy on the tissues in order to construct the biophotonic measurement system that meets the requirements of light safety regulations.
Biophotonics and electro-mechanical integration design is one of the key technologies for medical wearable products. In order to make the products efficient, accurate, durable, cost-effective, and provide a better user experience, product development and design need to consider the integration of technologies such as optics, mechanism, electronics, and software. In addition to improving product performance and efficiency to meet different medical needs and application scenarios, the ability to integrate opto-mechanical-electronic design is also an important factor for innovation and competitiveness.
To meet the individual needs of non-invasive optical measurement, we design and optimize optical sensors, such as selecting wavelengths, secondary optical design, and element layout, to improve detection efficiency and reduce noise. tBPC has established a complete precision optical development process with design, simulation, production, and validation experience, which can completely guide demand to mass production.
The physiological tissue model is established in the optical system and simulated simultaneously. This analysis not only confirms the optimal design of the sensor system before the optical system is implemented, but also adjusts the optical parameters of the physiological tissues and evaluates the effect of the optical system on different ethnic groups, physiological conditions, and diseases.
To have advanced Opto-Mechanical-Electronic integration development capabilities, such as for wearable medical devices, we need to consider the following two points:
1. Space optimization and miniaturization of components: Specialized components and systems that are lightweight, highly flexible, and comfortable. These devices require smaller and lighter components, as well as greater design flexibility to integrate technologies and provide more communication circuits. Ultra-miniature connectors and miniaturized components can provide more options in limited space and enhance the functionality of medical devices.
2. Enhance power and signal integrity: Ensure sufficient power and high signal integrity to deliver accurate patient data to healthcare organizations in a fast and timely manner. Therefore, it is important to design for both sufficient power and high signal integrity.
Medical algorithms play a crucial role in modern medicine, requiring not only a rigorous development process to ensure the accuracy of physiological parameters, but also the use of a large amount of clinical evidence data and a strict validation process to ensure their reliability. Therefore, medical algorithms can be applied to various aspects of diagnosis, prediction, treatment planning, and monitoring in smart healthcare to provide better medical services and healthcare.
For the purpose of developing highly accurate and error-tolerant algorithms, it is necessary to analyze and optimize physiological data for various conditions. Therefore, effective data acquisition is very critical, not only in different environments, but also taking into account the differences in ethnic populations, physiological conditions, and diseases, which requires extensive and large-scale collection of physiological data. tBPC has conducted many clinical trials and accumulated a large amount of systematic and effective data.
Medical algorithms must be interpretable and credible: Algorithm interpretability refers to the ability of an algorithm to explain to the user its internal logic and principles, as well as the basis and significance of its outputs. Algorithm credibility refers to the ability of an algorithm to gain the trust and acceptance of the user and to interact effectively with the user. Clinical validation is used by tBPC to ensure the interpretability and credibility of the algorithms, i.e., clinical validation is performed according to ISO, FDA regulations, or other professional standards, such as those of the Taiwan Society of Sleep Medicine and the American Heart Association.
Algorithm model is the core of the algorithm, which determines the function and performance of the algorithms. Algorithm development will involve appropriate feature engineering, model training, parameter tuning, model evaluation, and other steps, and continuously update and optimize the data iteration.
The algorithms by tBPC are equipped with the optimization capability for handling a large amount of data stacking as follows:
1. Automation: automatic input when collecting data, instead of manual key-in or manual transcription.
2. Elimination of repetitive tasks: including data classification and comparison, as well as de-identification.
3. Quick comparison and analysis of a large amount of data, elimination of erroneous data/and intelligent automatic error removal, and optimization of large data iteration.
4. Logic Analysis Program: construction of a logic analysis program according to artificial logic ideas, aiming at optimizing and completing the algorithm model.
5. Tools for predictive modeling and validation.
The oCare Wrist Pulse Oximeter, Model Pro 100, is a wrist-worn device indicated for use in noninvasive measuring, displaying, and storing functional oxygen saturation of arterial hemoglobin (% SpO2) and pulse rate (PR). The intended measuring site of this device is the wrist skin surface. It is intended for spot-checking or continuous monitoring of adult patients during no motion conditions, in hospitals, hospital-type facilities, and home environments.
To enable the wearable device to effectively detect physiological signals in the skin, tBPC has developed a reflective physiological sensor, which analyzes PPG signals by collecting the signals of reflection, penetration, scattering, and absorption of light waves through biological tissues. Biological tissues contain skin pigment, bone, and arterial and venous blood. When the arteries in the heart contract, blood increases, resulting in diameter expansion; conversely, when the heart is in diastole, blood decreases, resulting in diameter contraction. The use of light sensors to detect changes in blood vessel contraction is the PPG signal. Through the special design of the micro-lens and the DOE micro-structures, in addition to regulating the LED light into the tested tissues of the distribution of energy and increasing the efficiency of the light and light intensity, reduce stray light reflected directly from skin surface. This greatly improves the S/N ratio, reduces power consumption, and makes the device robust to movement interference.
Easy integration into mobile or wearable smart devices.
● | Ultra-small size, low power consumption, and high-performance System-on-Module (SoM). |
● | Optimal solution for mobile or wearable devices with pulse rate, respiration rate, and oxygen saturation level monitoring. |
Pulse rate, respiratory rate, and oxygen saturation concentration can be measured on a wider range of body parts, including fingers, toes, earlobes, wrists, chest, and forehead.
Directly measure the pulse rate, oxygen saturation concentration, and perfusion index values.
● | SoM with microprocessor control circuits and signal processing algorithms. |
● | Built-in high-performance reflective physiological sensors and 3-axis motion sensors. |
● | Provide accurate pulse rate, respiratory rate, oxygen saturation concentration, and perfusion index values directly to the host device via the I2C interface. |
Most common reflective PPG sensors consist of LEDs and photodiodes covered with an encapsulation layer of flat surface. They usually produce a light distribution curve with a wider half angle (i.e., 60 degrees). As shown in the following figure, the OCS112 is made with an innovative DOE structure. Each LED is separately encapsulated in a semi-spherical lens. The photodiode is covered by an encapsulation layer with a micro-structural surface. The light distribution curve emitted by the OCS112 is optimized to achieve higher PPG signal quality. Hence, the OCS112 shows higher lighting efficiency, focusing at the targeted body location.
tBPC’s own brand, “oCare Wrist Pulse Oximeter” is one of the world’s leading wearable medical devices. The technology of the DOE Reflectance patent is built-in, using specially designed micro-lenses and optical micro-structures for the optical sensors. The sensors are located in the lower cover of the core, which is an important contact surface between the wearable device and the human body, and therefore the design of the mechanism is also related to the quality of physiological signal reception. To make the detected physiological signals stable and complete, tBPC analyzed the PPG signals generated from the sensor area of the entire lower cover of the core and the skin model through biophotonic simulation, and further optimized the lower cover mechanism and the optical components to meet the high accuracy and stability requirements of wearable medical devices.
Physiological algorithm development is an analysis technology that converts PPG signals into physiological parameters, such as pulse rate, respiration, and blood oxygen saturation, with an accuracy that meets medical regulations. To establish the correct theory and filtering equations, it is also necessary to utilize a large amount of physiological data and analyze it against the gold standard to improve its accuracy and reliability. Since physiological data are collected through wearable devices, the algorithms have to be optimized to overcome all kinds of human differences, movements, shaking, and other disturbing factors. In addition, wearable medical devices need to be clinically validated to ensure that the analysis results of their algorithms comply with medical standards and specifications.