Human motion component and envelope characterization via wireless wearable sensors

Abstract

Background: The characterization of limb biomechanics has broad implications for analyzing and managing motion in aging, sports, and disease. Motion capture videography and on-body wearable sensors are powerful tools for characterizing linear and angular motions of the body, though are often cumbersome, limited in detection, and largely non-portable. Here we examine the feasibility of utilizing an advanced wearable sensor, fabricated with stretchable electronics, to characterize linear and angular movements of the human arm for clinical feedback. A wearable skin-adhesive patch with embedded accelerometer and gyroscope (BioStampRC, MC10 Inc.) was applied to the volar surface of the forearm of healthy volunteers. Arms were extended/flexed for the range of motion of three different regimes: 1) horizontal adduction/abduction 2) flexion/extension 3) vertical abduction. Data were streamed and recorded revealing the signal "pattern" of movement in three separate axes. Additional signal processing and filtering afforded the ability to visualize these motions in each plane of the body; and the 3dimensional motion envelope of the arm. Results: Each of the three motion regimes studied had a distinct patternwith identifiable qualitative and quantitative differences. Integration of all three movement regimes allowed construction of a "motion envelope," defining and quantifying motion (range and shapeincluding the outer perimeter of the extreme of motioni.e. the envelope) of the upper extremity. The linear and rotational motion results from multiple arm motions match measurements taken with videography and benchtop goniometer.Conclusions: A conformal, stretchable electronic motion sensor effectively captures limb motion in multiple degrees of freedom, allowing generation of characteristic signatures which may be readily recorded, stored, and analyzed. Wearable conformal skin adherent sensor patchs allow on-body, mobile, personalized determination of motion and flexibility parameters. These sensors allow motion assessment while mobile, free of a fixed laboratory environment, with utility in the field, home, or hospital. These sensors and mode of analysis hold promise for providing digital "motion biomarkers" of health and disease.

A Review of Recent Advances in Vital Signals Monitoring of Sports and Health via Flexible Wearable Sensors

“…To get rid of the discomfort caused by rigid inertial sensors, Ammann et al [ 71 ] implanted accelerometers and gyroscopes into the skin adhesive patch to develop a wireless and wearable motion tracking patch, as shown in Figure 5 a. They used the device to track the movement of the arms, and the obtained data was transmitted to a computer through Bluetooth.…”

“…Reprinted with permission from Ref. [ 71 ]. Copyright 2020 John Wiley and Sons, ( b ) optical images and an exploded view schematic illustration for a core/shell structure.…”

Capture of 3D Human Motion Pose in Virtual Reality Based on Video Recognition

“…A receiver composed of three ultrasonic probes (arranged in a triangle) receives the signal. It measures the time and phase difference when the ultrasonic waves are received by different receivers [29,30]. Since ultrasound has good penetrability, this acoustic solution has certain advantages; that is, it can solve the problem of blind spots caused by occlusion [31].…”

Biomechanics Beyond the Lab: Remote Technology for Osteoarthritis Patient Data - A Scoping Review

“…Identi ed commercially available technology with related corresponding information and study reference in which it was evaluated. to the information required from 3-axes data and related biomechanical models when compared to camera-based produced measures.Most IMUs were demonstrated as belt or strap worn devices, however, emerging in two studies(Ammann et al, 2020;Moon et al, 2017) is a commercially available skin adherent IMU; Biostamp (BiostampRC, M10 Inc. USA), found to be well suited to a variety of uses including potential granular monitoring of gait both inside and outside the clinic(Moon et al 2017). A variety of experimental systems were found reporting on IMU data collection alongside a mobile application(Aqueveque et al 2020, Li et al, 2020) and visual user-feedback (Bell et al, 2019) with good accuracy and platform outputs for joint angle measurements, demonstrating strong potential for reliable home-based rehabilitation data collection.…”