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Intelligent robotics in pediatric cooperative neurorehabilitation: a review
The landscape of neurorehabilitation is undergoing a profound transformation with the
integration of artificial intelligence (AI)-driven robotics. This review addresses the pressing …
integration of artificial intelligence (AI)-driven robotics. This review addresses the pressing …
[HTML][HTML] Worker's physical fatigue classification using neural networks
Physical fatigue is not only an indication of the user's physical condition and/or need for
sleep or rest, but can also be a significant symptom of various diseases. This fatigue affects …
sleep or rest, but can also be a significant symptom of various diseases. This fatigue affects …
Physiological characteristics predictive of passing military physical employment standard tasks for ground close combat occupations in men and women
Challenges for some women meeting the physical employment standards (PES) for ground
close combat (GCC) roles stem from physical fitness and anthropometric characteristics. The …
close combat (GCC) roles stem from physical fitness and anthropometric characteristics. The …
Gait Event Detection Based on Fuzzy Logic Model by Using IMU Signals of Lower Limbs
Y Liu, Y Liu, Q Song, D Wu, D ** - IEEE Sensors Journal, 2024 - ieeexplore.ieee.org
Gait event detection is an essential approach to execute accurate gait recognition, and many
studies use portable and reliable inertial measurement units (IMUs) for gait event detection …
studies use portable and reliable inertial measurement units (IMUs) for gait event detection …
[HTML][HTML] The effect of external loads and biological sex on coupling variability during load carriage
Background Load carriage is a fundamental requirement for military personnel that
commonly results in lower-limb injuries. Coupling variability represents a potential injury …
commonly results in lower-limb injuries. Coupling variability represents a potential injury …
A deep learning approach for human gait recognition from time-frequency analysis images of inertial measurement unit signal
Biomechanical analysis using deep learning has been increasingly used in recent studies to
identify human activity. Wearable sensor data from inertial measurement units (IMUs) is …
identify human activity. Wearable sensor data from inertial measurement units (IMUs) is …
Robust Personal Identification Using Wearable Devices Based on LSTM and CNN
J Choi, S Choi, T Kang - Journal of Sensors, 2023 - Wiley Online Library
Various studies exist to identify individuals. Personal identification research based on
inertial data, that is, acceleration and angular velocity acquired with an inertial sensor, is …
inertial data, that is, acceleration and angular velocity acquired with an inertial sensor, is …
[PDF][PDF] LSTM 을 사용한 보행주기 식별
최지우, 유형진, 최상일, 강태원 - 한국정보기술학회논문지, 2021 - ki-it.com
요 약보행주기에는 양쪽 발의 뒷굽 닿기 (HS) 와 발가락 떼기 (TO) 가 반복적으로 포함되어있다.
보행주기 식별은 해당 주기 내에 존재하는 양쪽 발의 HS 와 TO 를 찾는 작업이다. 본 …
보행주기 식별은 해당 주기 내에 존재하는 양쪽 발의 HS 와 TO 를 찾는 작업이다. 본 …
Biomechanical Effects of Foot Orthotics: A Machine Learning Approach
J Tiangco - 2024 - atrium.lib.uoguelph.ca
Foot orthotics are commonly prescribed to address lower limb conditions, yet understanding
their biomechanical effects remains elusive due to conflicting research findings. Traditional …
their biomechanical effects remains elusive due to conflicting research findings. Traditional …
Fractal Pattern Identification from Wearable Inertial and Electromyographic Signals Data during Walking
Acceleration, angular velocity and electromyographic (EMG) signal at the lower limb
muscles, specially over both leg's Tibialis Anterior muscles are highly non-stationary, even if …
muscles, specially over both leg's Tibialis Anterior muscles are highly non-stationary, even if …