Non-invasive hemoglobin concentration measurements with multi-wavelength reflectance mode PPG sensor and CNN data processing.

Possibility of non-invasive hemoglobin concentration measurements with wearable devices have been evaluated. The proposed solution is based on the assumption that PPG waveform shape measured at various wavelengths in the reflectance mode carries information about in-depth distribution of optical pathlength in the tissue. Decomposition of temporal and spectral features of PPG signal have been applied to correct estimation of hemoglobin concentration. The dataset including 840 PPG waveforms from 170 volunteers have been collected for the purpose of neural network training and validation. The achieved performance (MAE~13.6 g/l, R~0.62) is confirmed with the invasive blood test.Clinical Relevance - This paper establishes possibility of non-invasive real time hemoglobin concentration measurements by means of low-cost wearable sensor with accuracy comparable to non-invasive clinical instruments.

Multispectral sensor fusion in SmartWatch for in situ continuous monitoring of human skin hydration and body sweat loss.

Post-pandemic health operations have become a near-term reality, discussions around wearables are on the rise. How do wearable health solutions effectively deploy and use this opportunity to fill the gap between wellness and healthcare? In this paper, we will talk about wearable healthcare diagnosis, with a particular focus on monitoring skin hydration using optical multi-wavelength sensor fusion. Continuous monitoring of human skin hydration is a task of paramount importance for maintaining water loss dynamics for fitness lovers as well as for skin beauty, integrity and the health of the entire body. Preserving the appropriate levels of hydration ensures consistency of weight, positively affects psychological state, and proven to result in a decrease in blood pressure as well as the levels of "bad" cholesterol while slowing down the aging processes. Traditional methods for determining the state of water content in the skin do not allow continuous and non-invasive monitoring, which is required for variety of consumer, clinical and cosmetic applications. We present novel sensing technology and a pipeline for capturing, modeling and analysis of the skin hydration phenomena and associated changes therein. By expanding sensing capabilities built into the SmartWatch sensor and combining them with advanced modeling and Machine Learning (ML) algorithms, we identified several important characteristics of photoplethysmography (PPG) signal and spectral sensitivity corresponding to dynamics of skin water content. In a hardware aspect, we newly propose the expansion of SmartWatch capabilities with InfraRed light sources equipped with wavelengths of 970 nm and 1450 nm. Evaluation of the accuracy and characteristics of PPG sensors has been performed with biomedical optics-based simulation framework using Monte Carlo simulations. We performed rigorous validation of the developed technology using experimental and clinical studies. The developed pipeline serves as a tool in the ongoing studies of the next generation of optical sensing technology.

Stretchable PPG sensor with light polarization for physical activity-permissible monitoring.

Skin-attachable sensors, which represent the ultimate form of wearable electronic devices that ensure conformal contact with skin, suffer from motion artifact limitations owing to relative changes in position between the sensor and skin during physical activities. In this study, a polarization-selective structure of a skin-conformable photoplethysmographic (PPG) sensor was developed to decrease the amount of scattered light from the epidermis, which is the main cause of motion artifacts. The motion artifacts were suppressed more than 10-fold in comparison with those of rigid sensors. The developed sensor-with two orthogonal polarizers-facilitated successful PPG signal monitoring during wrist angle movements corresponding to high levels of physical activity, enabling continuous monitoring of daily activities, even while exercising for personal health care.

Mind Your Composition: Clinical validation of Samsung's pocket-based bioelectrical impedance analyzers may increase consumer interest in personal health management.

When asked about our weight, most of us can name a figure based on prior knowledge. And while stepping on a scale gives us the ability to know that exact number and track it routinely, it does not provide insights into our body?s composition. This, at the basic level, refers to proportions of fat and lean or fat-free mass (FFM) that comprise the human body. Conventionally, the body mass index (BMI), which is the ratio of body weight in kilograms to the square of its height in meters, and anthropometric parameters like waist circumference, waist-to-hip ratio, and skinfold thickness have been used to estimate the level of fatness. In fact, BMI is the de facto marker for stratifying individuals into underweight (<18.5 kg/m2), normal (18.5-24.9 kg/m2), overweight (25-29.9 kg/m2), and obese (>30 kg/m2) categories. Nonetheless, these metrics are limited in precisely characterizing individuals by percentages of body fat and muscle mass, particularly in epidemiological studies where these proportions vary across age, sex, and ethnic groups. Of note is also how, solely on the basis of BMI, a physically fit individual may be classified as overweight due to having a higher proportion of lean body mass, which outweighs fat. This highlights the importance of body composition in weight tracking and management.

Smartphone-Based Bioelectrical Impedance Analysis Devices for Daily Obesity Management.

Current bioelectric impedance analysis (BIA) systems are often large, cumbersome devices which require strict electrode placement on the user, thus inhibiting mobile capabilities. In this work, we developed a handheld BIA device that measures impedance from multiple frequencies (5 kHz~200 kHz) with four contact electrodes and evaluated the BIA device against standard body composition analysis systems: a dual-energy X-ray absorptiometry (DXA) system (GE Lunar Prodigy, GE Healthcare, Buckinghamshire, UK) and a whole-body BIA system (InBody S10, InBody, Co. Ltd, Seoul, Korea). In the study, 568 healthy participants, varying widely in body mass index, age, and gender, were recruited at two research centers: the Samsung Medical Center (SMC) in South Korea and the Pennington Biomedical Research Center (PBRC) in the United States. From the measured impedance data, we analyzed individual body fat and skeletal muscle mass by applying linear regression analysis against target reference data. Results indicated strong correlations of impedance measurements between the prototype pathways and corresponding InBody S10 electrical pathways (R = 0.93, p < 0.0001). Additionally, body fat estimates from DXA did not yield significant differences (p > 0.728 (paired t-test), DXA mean body fat 29.45 ± 10.77 kg, estimated body fat 29.52 ± 12.53 kg). Thus, this portable BIA system shows a promising ability to estimate an individual's body composition that is comparable to large stationary BIA systems.

Mobile evaluation of human energy balance and weight control: Potential for future developments.

Quantification of energy storage is essential in understanding energy balance and can be determined by bioelectrical impedance analysis (BIA). Here, we have developed a smartphone form factor multi-frequency BIA device that incorporates an analog front end for body composition measurements. The device was compared against a reference gel-electrode based BIA system in a clinical trial of 311 subjects for predicting BIA equations by calibrating the impedance index to body composition data from dual energy X-ray absorptiometry (DXA). Strong correlations were observed between DXA-based lean soft tissue and the impedance index generated at 50 KHz (R(2)=0.87; p<;0.001). A similar trend was also evident at higher frequencies which matched results from the reference gel-electrode BIA device. The findings support the role of our consumer-oriented mobile Health initiative for multi-frequency BIA assessments to aid weight management.