Evidence map›Paper›PMID 35336583›Full record

ArticleSensors (Basel, Switzerland)2022

Sensing System for Plegic or Paretic Hands Self-Training Motivation.

Igor Zubrycki, Ewa Prączko-Pawlak, Ilona Dominik

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 43% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Trial
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Igor ZubryckiInstitute of Automatic Control, Lodz University of Technology, Stefanowskiego 18, 90-537 Lodz, Poland.ORCID 0000-0002-1229-2173
Ewa Prączko-PawlakMiejskie Centrum Medyczne im. dr Karola Jonschera, Milionowa 14, 93-113 Lodz, Poland.ORCID 0000-0002-0423-6614
Ilona DominikInstitute of Automatic Control, Lodz University of Technology, Stefanowskiego 18, 90-537 Lodz, Poland.ORCID 0000-0002-5764-5817
Lodz University of Technology · PL

Funding

National Centre for Research and Development LIDER/50/0203/L-11/19/NCBR/2020
6 · The paper itself

Abstract

Patients after stroke with paretic or plegic hands require frequent exercises to promote neuroplasticity and to improve hand joint mobilization. Available devices for hand exercising are intended for persons with some level of hand control or provide continuous passive motion with limited patient involvement. Patients can benefit from self-exercising where they use the other hand to exercise the plegic or paretic one. However, post-stroke neuropsychological complications, apathy, and cognitive impairments such as forgetfulness make regular self-exercising difficult. This paper describes Przypominajka v2-a system intended to support self-exercising, remind about it, and motivate patients. We propose a glove-based device with an on-device machine-learning-based exercise scoring, a tablet-based interface, and a web-based application for therapists. The feasibility of on-device inference and the accuracy of correct exercise classification was evaluated on four healthy participants. Whole system use was described in a case study with a patient with a paretic hand. The anomaly classification has an accuracy of 91.3% and f1 value of 91.6% but achieves poorer results for new users (78% and 81%). The case study showed that patients had a positive reaction to exercising with Przypominajka, but there were issues relating to sensor glove: ease of putting on and clarity of instructions. The paper presents a new way in which sensor systems can support the rehabilitation of after-stroke patients with an on-device machine-learning-based classification that can accurately score and contribute to patient motivation.

Indexed as

MotivationStrokeHandHumansMovementRange of Motion, ArticularInternet of Medical Thingsparesisplegiasensor glovesensor systemstrokestroke rehabilitationwearable device

Identifiers

PMID35336583
PMCPMC8955878
OpenAlexW4221073882

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.