Related papers: Adaptive and robust smartphone-based step detectio…
With an aging population, numerous assistive and monitoring technologies are under development to enable older adults to age in place. To facilitate aging in place predicting risk factors such as falls, and hospitalization and providing…
In-home gait analysis is important for providing early diagnosis and adaptive treatments for individuals with gait disorders. Existing systems include wearables and pressure mats, but they have limited scalability. Recent studies have…
The objective assessment of gait kinematics is crucial in evaluating human movement, informing clinical decisions, and advancing rehabilitation and assistive technologies. Assessing gait symmetry, in particular, holds significant importance…
We introduce Walk4Me, a telehealth community mobility assessment system designed to facilitate early diagnosis, severity, and progression identification. Our system achieves this by 1) enabling early diagnosis, 2) identifying early…
Previous gait phase detection as convolutional neural network (CNN) based classification task requires cumbersome manual setting of time delay or heavy overlapped sliding windows to accurately classify each phase under different test cases,…
Movement directly reflects neurological and musculoskeletal health, yet objective biomechanical assessment is rarely available in routine care. We introduce Portable Biomechanics Laboratory (PBL), a secure platform for fitting biomechanical…
The study of biomechanics during locomotion provides valuable insights into the effects of varying conditions on specific movement patterns. This research focuses on examining the influence of different shoe parameters on walking…
Objective: In this paper, we demonstrate the applicability of radar for gait classification with application to home security, medical diagnosis, rehabilitation and assisted living. Aiming at identifying changes in gait patterns based on…
Current gait analysis faces challenges in various aspects, including limited and poorly labeled data within existing wearable electronics databases, difficulties in collecting patient data due to privacy concerns, and the inadequacy of the…
Physical activity is recognized as an essential component of overall health. One measure of physical activity, the step count, is well known as a predictor of long-term morbidity and mortality. Step Counting (SC) is the automated counting…
Gait encodes rich biometric and behavioural information, yet leveraging the manner of walking to infer psychological traits remains a challenging and underexplored problem. We introduce a hierarchical Multi-Stage Mixture of Movement Experts…
Gait assessment is a key clinical indicator of fall risk and overall health in older adults. However, standard clinical practice is largely limited to stopwatch-measured gait speed. We present a pipeline that leverages a 3D Human Mesh…
Quantifying step abundance via single wrist-worn accelerometers is a common approach for encouraging active lifestyle and tracking disease status. Nonetheless, step counting accuracy can be hampered by fluctuations in walking pace or…
Gait velocity has been consistently shown to be an important indicator and predictor of health status, especially in older adults. It is often assessed clinically, but the assessments occur infrequently and do not allow optimal detection of…
Elderly gait is a source of rich information about their physical and mental health condition. As an alternative to the multiple sensors on the lower body parts, a single sensor on the pelvis has a positional advantage and an abundance of…
Personal devices have adopted diverse authentication methods, including biometric recognition and passcodes. In contrast, headphones have limited input mechanisms, depending solely on the authentication of connected devices. We present…
Here, we present IDNet, a user authentication framework from smartphone-acquired motion signals. Its goal is to recognize a target user from their way of walking, using the accelerometer and gyroscope (inertial) signals provided by a…
The applicability of Doppler radar for gait analysis is investigated by quantitatively comparing the measured biomechanical parameters to those obtained using motion capturing and ground reaction forces. Nineteen individuals walked on a…
Objective. Using raw, sub-second level, accelerometry data, we propose and validate a method for identifying and characterizing walking in the free-living environment. We focus on the sustained harmonic walking (SHW), which we define as…
Accelerometer signals generated through gait present a new frontier of human interface with mobile devices. Gait cycle detection based on these signals has applications in various areas, including authentication, health monitoring, and…