Objectivizing measures of post-stroke hand rehabilitation through multi-disciplinary scales

K Marek, J Redlicka, E Miller, I Zubrycki - Journal of Clinical Medicine, 2023 - mdpi.com
There is a wide variety of tools and measures for rehabilitation outcomes in post-stroke
patients with impairments in the upper limb and hand, such as paralysis, paresis, flaccidity …

Machine learning prediction of motor function in chronic stroke patients: a systematic review and meta-analysis

Q Li, L Chi, W Zhao, L Wu, C Jiao, X Zheng… - Frontiers in …, 2023 - frontiersin.org
Background Recent studies have reported that machine learning (ML), with a relatively
strong capacity for processing non-linear data and adaptive ability, could improve the …

A novel approach for upper limb functionality assessment based on deep learning and multimodal sensing data

S Miao, Y Dang, Q Zhu, S Li, M Shorfuzzaman… - IEEE Access, 2021 - ieeexplore.ieee.org
Upper limb rehabilitation is an effective methodology to restore and improve the functionality
of patients after multiple medical events, such as strokes, arthroscopic surgery, and breast …

Task-Oriented Training by a Personalized Electromyography-Driven Soft Robotic Hand in Chronic Stroke: A Randomized Controlled Trial

XQ Shi, CHE Ti, HY Lu, CP Hu, DS Xie… - … and Neural Repair, 2024 - journals.sagepub.com
Background Intensive task-oriented training has shown promise in enhancing distal motor
function among patients with chronic stroke. A personalized electromyography (EMG)-driven …

An assessment system for post-stroke manual dexterity using principal component analysis and logistic regression

BS Lin, IJ Lee, PC Hsiao… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
Hand function assessment is crucial for patients with stroke, who must perform regular
repetitive tasks during rehabilitation. However, the conventional evaluation method is …

Supervised myoelectrical hand gesture recognition in post-acute stroke patients with upper limb paresis on affected and non-affected sides

A Anastasiev, H Kadone, A Marushima, H Watanabe… - Sensors, 2022 - mdpi.com
In clinical practice, acute post-stroke paresis of the extremities fundamentally complicates
timely rehabilitation of motor functions; however, recently, residual and distorted …

Ηand dexterities assessment in stroke patients based on augmented reality and machine learning through a box and block test

G Papagiannis, Α Triantafyllou, KG Yiannopoulou… - Scientific Reports, 2024 - nature.com
A popular and widely suggested measure for assessing unilateral hand motor skills in stroke
patients is the box and block test (BBT). Our study aimed to create an augmented reality …

Neurocognitive robot-assisted rehabilitation of hand function: a randomized control trial on motor recovery in subacute stroke

R Ranzani, O Lambercy, JC Metzger, A Califfi… - … of neuroengineering and …, 2020 - Springer
Background Hand function is often impaired after stroke, strongly affecting the ability to
perform daily activities. Upper limb robotic devices have been developed to complement …

Development of LSTM&CNN based hybrid deep learning model to classify motor imagery tasks

C Uyulan - bioRxiv, 2020 - biorxiv.org
Recent studies underline the contribution of brain-computer interface (BCI) applications to
the enhancement process of the life quality of physically impaired subjects. In this context, to …

Deep learning analysis based on multi-sensor fusion data for hemiplegia rehabilitation training system for stoke patients

P Zhang, J Zhang - Robotica, 2022 - cambridge.org
By recognizing the motion of the healthy side, the lower limb exoskeleton robot can provide
therapy to the affected side of stroke patients. To improve the accuracy of motion intention …