Hand Flexibility Assessment System Study Based on Pneumatic Actuation and Sensing

ObjectiveTo develop a hand flexibility assessment system based on pneumatic actuation and sensing, and validate its accuracy and reliability. The system aims to provide a scientific basis for solving the problem of hand flexibility assessment and developing hand rehabilitation training plans.MethodsA pneumatic-driven assessment system consisting of pneumatic actuation modules, circuit boards, data feedback modules, and human-computer interaction modules is designed. The system uses air pressure as a quantitative indicator to assess hand flexibility. Based on the data collection needs of patients with varying degrees of hand dysfunction, four impedance evaluation modes with different intensities (mild, moderate, severe, and very severe) are designed. The soft actuator produces unilateral bending or relaxation through air inflation and deflation. During multiple finger flexions by the user, an opposing effect is generated between the user and the system. The air pressure inside the soft actuator is recorded in real time, providing data for hand flexibility assessment. Hand flexibility is quantified by combining the Brunnstrom hand function stage scale and the Total Active Motion (TAM) assessment method. Healthy subjects' test data are recorded and used as a template. The air pressure data of eight patients with hand dysfunction are collected for hand flexibility evaluation and compared with the results of three attending physicians from a rehabilitation center to verify the system’s accuracy in assessing hand flexibility.ResultsThe average air pressure change was maintained around 10 kPa for healthy subjects performing group impedance flexion tests. In 10 repeated experiments, the standard deviations of test results for the four intensity levels (mild, moderate, severe, very severe) were 0.37535, 0.27961, 0.39354, and 0.32010, respectively. During group impedance extension tests, the average air pressure change was maintained around 6 kPa, with standard deviations for the four intensity levels of 0.40442, 0.26102, 0.22012, and 0.13050, respectively, in 10 repeated experiments. For patients 1 and 2, based on the Brunnstrom evaluation scale, their finger recovery stages were determined to be Stage I and Stage II, respectively. For patients 3 and 4, the air pressure change was around 1 kPa. Patient 3 demonstrated better finger flexibility than patient 4. Patients 5 to 8 were evaluated using the TAM method, and patient 8 was classified with good hand flexibility, while the others were rated as poor.ConclusionThe system shows high accuracy and reliability in assessing hand flexibility and has the potential to replace rehabilitation physicians in quantitatively evaluating hand flexibility.

Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2025-04-01
Primary Topic
Stroke Rehabilitation and Recovery
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Hand Flexibility Assessment System Study Based on Pneumatic Actuation and Sensing

SHILAP Revista de lepidopterología
Stroke Rehabilitation and Recovery
article

Hand Flexibility Assessment System Study Based on Pneumatic Actuation and Sensing

article en

Abstract

ObjectiveTo develop a hand flexibility assessment system based on pneumatic actuation and sensing, and validate its accuracy and reliability. The system aims to provide a scientific basis for solving the problem of hand flexibility assessment and developing hand rehabilitation training plans.MethodsA pneumatic-driven assessment system consisting of pneumatic actuation modules, circuit boards, data feedback modules, and human-computer interaction modules is designed. The system uses air pressure as a quantitative indicator to assess hand flexibility. Based on the data collection needs of patients with varying degrees of hand dysfunction, four impedance evaluation modes with different intensities (mild, moderate, severe, and very severe) are designed. The soft actuator produces unilateral bending or relaxation through air inflation and deflation. During multiple finger flexions by the user, an opposing effect is generated between the user and the system. The air pressure inside the soft actuator is recorded in real time, providing data for hand flexibility assessment. Hand flexibility is quantified by combining the Brunnstrom hand function stage scale and the Total Active Motion (TAM) assessment method. Healthy subjects' test data are recorded and used as a template. The air pressure data of eight patients with hand dysfunction are collected for hand flexibility evaluation and compared with the results of three attending physicians from a rehabilitation center to verify the system’s accuracy in assessing hand flexibility.ResultsThe average air pressure change was maintained around 10 kPa for healthy subjects performing group impedance flexion tests. In 10 repeated experiments, the standard deviations of test results for the four intensity levels (mild, moderate, severe, very severe) were 0.37535, 0.27961, 0.39354, and 0.32010, respectively. During group impedance extension tests, the average air pressure change was maintained around 6 kPa, with standard deviations for the four intensity levels of 0.40442, 0.26102, 0.22012, and 0.13050, respectively, in 10 repeated experiments. For patients 1 and 2, based on the Brunnstrom evaluation scale, their finger recovery stages were determined to be Stage I and Stage II, respectively. For patients 3 and 4, the air pressure change was around 1 kPa. Patient 3 demonstrated better finger flexibility than patient 4. Patients 5 to 8 were evaluated using the TAM method, and patient 8 was classified with good hand flexibility, while the others were rated as poor.ConclusionThe system shows high accuracy and reliability in assessing hand flexibility and has the potential to replace rehabilitation physicians in quantitatively evaluating hand flexibility.

SHILAP Revista de lepidopterología
Openalex Percentile: Top 44%
Stroke Rehabilitation and Recovery
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.