Search

Background: Patients with stroke often experience weakened upper limbs, making daily tasks difficult to perform. Although rehabilitation devices are available, patients often relapse post-discharge due to insufficient practice. We present a home-based hand telerehabilitation intervention using the iManus™ platform comprising a sensorized glove, a mobile app for the patients, and a therapist portal for monitoring patient progress. Objectives: This research aimed to examine the feasibility, safety, and effectiveness of a home-based telerehabilitation intervention in improving hand function for individuals with mild stroke. A qualitative approach was also used to explore users' experiences, perceived benefits, and challenges associated with using the platform in a home setting. Methods: In this single-case study, we delivered a hand telerehabilitation intervention to a chronic stroke patient with impaired hand function using the iManus™ platform. The intervention consisted of 40 home sessions over eight weeks. We assessed feasibility through user adherence and feedback obtained using a System Usability Scale (SUS) and a semi-structured interview with the participant and their informal caregiver. Safety was evaluated by monitoring pain levels using the Visual Analog Scale (VAS), and efficacy was determined by observing the changes in the fingers’ range of motion using the iManus™ platform and clinical outcomes measures, namely the Fugl-Meyer Assessment (FMA) and Jebsen Taylor Hand Function Test (JTHFT). Results: Our participant completed all the assigned sessions, with each averaging 20 min. Usability scored 77.5 out of 100 on the SUS. User feedback from the interviews revealed improved mobility and control over therapy as benefits, indicating room for improvement in the intervention's adaptability and functionality. During the intervention, the participant noted no pain increase, and the telerehabilitation platform recorded range of motion improvements for all finger and wrist joints, excluding wrist extension. The FMA scores were 43 at T0, 53 at T1, and 56 at T2, while the JTHFT scores were 223 at T0, 188 at T1, and 240 at T2. Conclusions: This single case study demonstrated the preliminary feasibility, safety, and efficacy of a novel home-based hand intervention for stroke survivors. The participant showed improved hand functions, good adherence to the program, and reported satisfaction with the intervention. However, these results are based on a single-case study, and further large-scale studies are needed before any generalization is recommended.

The advent of deep learning has pushed medical image analysis to new levels, rapidly replacing more traditional machine learning and computer vision pipelines. However segmenting and labelling anatomical regions remains challenging owing to appearance variations, imaging artifacts, the paucity and variability of annotated data, and the difficulty of fully exploiting domain constraints such as anatomical knowledge about inter-region relationships. We address the last point, improving the network's region-labeling consistency by introducing NonAdjLoss, an adjacency-graph based auxiliary training loss that penalizes outputs containing regions with anatomically-incorrect adjacency relationships. NonAdjLoss supports both fully-supervised training and a semi-supervised extension in which it is applied to unlabeled supplementary training data. The approach substantially reduces segmentation anomalies on the MICCAI-2012, IBSRv2 brain MRI datasets and the Anatomy3 whole body CT dataset, especially when semi-supervised training is included., (Copyright © 2019. Published by Elsevier B.V.)