Results 231 to 240 of about 50,085 (299)

Response Characteristics of Key Filtering Parameters and Applicability of Interference Detection for Integrated Navigation Under Spoofing Interference. [PDF]

Sensors (Basel)
Zhao S, Fu J, Li B, Jiang P.
europepmc   +1 more source

A Flexible Self‐Powered Wearable Strain Sensor for Real‐Time Gait Recognition and Cooperative Control of Lower‐Limb Exoskeletons

SmartSys, Volume 2, Issue 3, September 2026.
ABSTRACT Real‐time monitoring of subtle muscle deformation remains of considerable importance for cooperative human‐exoskeleton control. Highly integrated flexible triboelectric nanogenerators (TENGs), owing to their self‐powered operation and high sensing resolution, are well suited for continuous physiological monitoring and human‐robot interaction ...
Heran Li, Jiange Kou, Xianpeng Fu, Zhiguo Yang, Xiangkai Shen, Zhibo Sun, Yixuan Wang, Yan Shi, Chi Zhang, Fei Xie   +9 more
wiley   +1 more source

Assessment of IMU-derived lower-limb kinematics in transtibial amputees: A practical and accessible clinical workflow. [PDF]

PLoS One
Rattanakoch J, Limroongreungrat W, Guerra G, Manupibul U, Apidech H, Niamsang W, Suphab M, Laucha T, Samala M.   +8 more
europepmc   +1 more source

Quantifying the Equine Pain Response to Paracetamol Administration in Horses With Chronic Lameness Already Receiving Non‐Steroidal Anti‐Inflammatories

Veterinary Medicine and Science, Volume 12, Issue 5, September 2026.
In geriatric horses with chronic lameness receiving NSAIDs, adjunct oral paracetamol (20 mg/kg BID) showed no significant improvement in lameness severity. Weekly subjective scoring and objective gait analysis revealed no differences versus baseline or post‐treatment, indicating limited additional analgesic benefit in this population.
Stefanie Conduit, Mark Bowen, James Bailey, Adam Redpath   +3 more
wiley   +1 more source

Vision-based vs. IMU-based upper-limb pose estimation in assisted dressing: a comparative study of positional accuracy and kinematic fidelity. [PDF]

Front Robot AI
Rafiq Y, Wang S, Al-Nuaimi M, Mihaylova L, Hierons RM, Dogramadzi S.   +5 more
europepmc   +1 more source

Artificial Intelligence in Veterinary Neurology: Comparative Insights From Human Medicine and Cross‐Species Technology Transfer

Veterinary Medicine and Science, Volume 12, Issue 5, September 2026.
Overview of major artificial intelligence applications in veterinary neurology, including neuroimaging, seizure prediction, gait and pain assessment, and prognostic modeling. The figure also highlights cross‐species technology transfer and key challenges, such as limited data, lack of standardization, and ethical concerns.
Kianoush Saberi, Rosull Saadoon Abbood, Sarah F. Al‐Taie, Aseel Smerat, Abdullaev Makhmudjon Mukhamedovich, Maksudova Malika Khamdamjonovna, Mohammad Hedayatinia, Arash Zarei, Mehrdad Nourizadeh, Amir Arsalan Ghahari, Mehrdad Neshat Gharamaleki, Fatemeh Malekinejad, Reza Akhavan‐Sigari   +12 more
wiley   +1 more source

MoCap-Referenced Neck-Shoulder sEMG-IMU Decoding for Discrete Assistive Commands: A Pilot Study. [PDF]

Sensors (Basel)
Majeed AH, Masood F, Abdullah HA.
europepmc   +1 more source

A Systematic Review and Taxonomy of Fall Detection in Geriatric Care: Current State, Challenges, and Applications

WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 3, September 2026.
Overview of fall‐detection approaches and technologies in geriatric care. ABSTRACT This systematic review provides a critical examination of fall detection (FD) technologies in geriatric care, analyzing both technological innovations and implementation challenges across diverse healthcare environments.
Hamid Ali, Ji Zhang, Xiaohui Tao, Raj Gururajan, Xujuan Zhou, Yuquan Gan, Josh Jia‐Ching Ying   +6 more
wiley   +1 more source

IMU-based workspace area as a promising complementary tool to assess upper limb function in Neuromuscular diseases: A one-year follow-up. [PDF]

J Neuromuscul Dis
Favata A, Expósito-Escudero J, Gallart-Agut R, Medina-Cantillo J, Torras C, Font-Llagunes JM, Pàmies-Vilà R, Natera-de Benito D.   +7 more
europepmc   +1 more source

Quantifying microhabitat selection of snowshoe hares using forest metrics from UAS‐based LiDAR

Wildlife Biology, Volume 2026, Issue 5, September 2026.
Identifying the spatial and temporal scale at which animals select resources is critical for predicting how populations respond to changes in the environment. The spatial distribution of fine‐scale resources (e.g. patches of dense vegetation) are often linked with critical life‐history requirements such as denning and feeding sites.
Alexej P. K. Sirén, Franklin Sullivan, Rachel Cliché, Jeremy Goetz, Leighlan S. Prout, Jillian Kilborn, Katelyn Courtot, Michael Palace   +7 more
wiley   +1 more source