Intelligent robotics in pediatric cooperative neurorehabilitation: a review

E Ezra Tsur, O Elkana - Robotics, 2024 - mdpi.com
The landscape of neurorehabilitation is undergoing a profound transformation with the
integration of artificial intelligence (AI)-driven robotics. This review addresses the pressing …

[HTML][HTML] Worker's physical fatigue classification using neural networks

E Escobar-Linero, M Domínguez-Morales… - Expert Systems with …, 2022 - Elsevier
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 …

Physiological characteristics predictive of passing military physical employment standard tasks for ground close combat occupations in men and women

ED Feigel, AJ Sterczala, KT Krajewski… - European Journal of …, 2024 - Wiley Online Library
Challenges for some women meeting the physical employment standards (PES) for ground
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 …

[HTML][HTML] The effect of external loads and biological sex on coupling variability during load carriage

B Hoolihan, J Wheat, B Dascombe, D Vickery-Howe… - Gait & posture, 2023 - Elsevier
Background Load carriage is a fundamental requirement for military personnel that
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

H Kuduz, F Kaçar - International Journal of Applied Methods in …, 2023 - ijamec.org
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 …

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 …

[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 …

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 …

Fractal Pattern Identification from Wearable Inertial and Electromyographic Signals Data during Walking

SM Rahman, MA Al Mamun… - 2022 25th International …, 2022 - ieeexplore.ieee.org
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 …