Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form

Tuning algorithms for control interfaces for users with upper-limb impairments

Guirand, AS and Dicianno, BE and Mahajan, H and Cooper, RA (2011) Tuning algorithms for control interfaces for users with upper-limb impairments. American Journal of Physical Medicine and Rehabilitation, 90 (12). 992 - 998. ISSN 0894-9115

[img] Plain Text (licence)
Available under License : See the attached license file.

Download (1kB)

Abstract

Objective: Approximately 40% of Americans with disabilities cannot operate wheeled mobility devices and computers adequately because of diminished upper-limb motor control, sensory limitations, and cognitive impairments. We developed tuning software that can customize control interfaces for individuals with upper-limb impairments. This study compared the differences in each parameter among different diagnostic groups. Design: The age of the subjects ranged from 18 to 80 yrs. The participants were classified into the following groups: athetoid cerebral palsy, spastic cerebral palsy, multiple sclerosis, upper-limb spasticity, and control. We used a validated tuning software protocol to customize an isometric joystick before a virtual tracing or driving task. Tuning parameters were then compared across groups. Results: Seventy-five subjects were included. Gain, the parameter responsible for force-to-output ratios, in each directional axis (leftward gain: P = 0.018; rightward gain: P = 0.003; reverse gain: P = 0.007; forward gain: P = 0.014) was significantly different across the diagnostic groups. Post hoc analyses showed that the control group required smaller leftward gain than spastic cerebral palsy, multiple sclerosis and upper-limb spasticity groups and smaller gain in all other directions compared with spastic cerebral palsy. Conclusions: Gain may be a useful parameter in tuning by clinicians, and efforts aimed at gain customization may aid the development of commercially available tuning software packages. Copyright © 2011 by Lippincott Williams & Wilkins.


Share

Citation/Export:
Social Networking:
Share |

Details

Item Type: Article
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Guirand, AS
Dicianno, BEdicianno@pitt.eduDICIANNO0000-0003-0738-0192
Mahajan, H
Cooper, RARCOOPER@pitt.eduRCOOPER
Centers: Other Centers, Institutes, Offices, or Units > Human Engineering Research Laboratories
Date: 1 December 2011
Date Type: Publication
Journal or Publication Title: American Journal of Physical Medicine and Rehabilitation
Volume: 90
Number: 12
Page Range: 992 - 998
DOI or Unique Handle: 10.1097/phm.0b013e318228ca9f
Schools and Programs: School of Health and Rehabilitation Sciences > Rehabilitation Science and Technology
Refereed: Yes
ISSN: 0894-9115
MeSH Headings: Adolescent; Adult; Aged; Aged, 80 and over; Algorithms; Brain Injuries--diagnosis; Brain Injuries--rehabilitation; Case-Control Studies; Cerebral Palsy--diagnosis; Cerebral Palsy--rehabilitation; Cohort Studies; Disability Evaluation; Disabled Persons--rehabilitation; Equipment Design; Female; Humans; Male; Middle Aged; Multiple Sclerosis--diagnosis; Multiple Sclerosis--rehabilitation; Neuromuscular Diseases--diagnosis; Neuromuscular Diseases--rehabilitation; Parkinson Disease--diagnosis; Parkinson Disease--rehabilitation; Reference Values; Self-Help Devices--utilization; Software; Upper Extremity--physiopathology; User-Computer Interface; Young Adult
Other ID: NLM NIHMS311106 [Available on 12/01/12], NLM PMC3217060 [Available on 12/01/12]
PubMed Central ID: PMC3217060
PubMed ID: 22019961
Date Deposited: 12 Oct 2012 18:37
Last Modified: 05 Feb 2019 00:55
URI: http://d-scholarship-dev.library.pitt.edu/id/eprint/15710

Metrics

Monthly Views for the past 3 years

Plum Analytics

Altmetric.com


Actions (login required)

View Item View Item