Assistive technologies: Can they contribute to rehabilitation of the upper limb after stroke?

Authors: Farmer, S.E., Durairaj, V., Swain, I. and Pandyan, A.D.

Journal: Archives of Physical Medicine and Rehabilitation

Volume: 95

Issue: 5

Pages: 968-985

eISSN: 1532-821X

ISSN: 0003-9993

DOI: 10.1016/j.apmr.2013.12.020

Abstract:

Objective To systematically identify, review, and explore the evidence for use of assistive technologies (ATs) in poststroke upper limb rehabilitation. Data Sources AMED, CINAHL, Cochrane Library, Compendex, CSA Illumina, EMBASE, MEDLINE, PEDro, PyscINFO, and Web of Science were last searched in September 2011. Study Selection Two independent researchers screened for inclusion criteria (adult poststroke subjects, upper limb rehabilitation with an AT). The risk of bias was assessed. Randomized controlled trials of poststroke subjects with baseline equivalence as assessed by blinded assessors were selected for data extraction. Data Extraction Details of subjects, experimental and control treatments, and all outcomes were recorded in a spreadsheet. Data Synthesis These data were used to calculate effect sizes for all outcome measures. Impairment measures ranged from -.39 (95% confidence interval [CI], -1.14 to.62) to 1.46 (95% CI,.72-2.20). Measures of activity effect sizes were from.04 (95% CI, -.35 to.44) to.93 (95% CI, -.39 to 2.25); for Motor Activity Log, from.07 (95% CI, -.66 to.80) to 1.24 (95% CI,.47-2.01); and for participation, from -3.32 (95% CI, -4.52 to 2.11) to 1.78 (95% CI, 0-3.56). Conclusions AT treatments appear to give modest additional benefit when compared with usual care or in addition to usual care. This is most apparent for subjects early poststroke with 2 caveats: high-intensity constraint-induced movement therapy and electrical stimulation exclusively to the shoulder appear detrimental. The heterogeneity of treatment parameters and population characteristics precludes specific recommendations. Research would benefit from modeling studies to explicitly define criteria of population, intervention, comparator, and outcomes for effective treatments before the development of efficiently integrated care pathways. © 2014 by the American Congress of Rehabilitation Medicine.

Source: Scopus

Assistive technologies: can they contribute to rehabilitation of the upper limb after stroke?

Authors: Farmer, S.E., Durairaj, V., Swain, I. and Pandyan, A.D.

Journal: Arch Phys Med Rehabil

Volume: 95

Issue: 5

Pages: 968-985

eISSN: 1532-821X

DOI: 10.1016/j.apmr.2013.12.020

Abstract:

OBJECTIVE: To systematically identify, review, and explore the evidence for use of assistive technologies (ATs) in poststroke upper limb rehabilitation. DATA SOURCES: AMED, CINAHL, Cochrane Library, Compendex, CSA Illumina, EMBASE, MEDLINE, PEDro, PyscINFO, and Web of Science were last searched in September 2011. STUDY SELECTION: Two independent researchers screened for inclusion criteria (adult poststroke subjects, upper limb rehabilitation with an AT). The risk of bias was assessed. Randomized controlled trials of poststroke subjects with baseline equivalence as assessed by blinded assessors were selected for data extraction. DATA EXTRACTION: Details of subjects, experimental and control treatments, and all outcomes were recorded in a spreadsheet. DATA SYNTHESIS: These data were used to calculate effect sizes for all outcome measures. Impairment measures ranged from -.39 (95% confidence interval [CI], -1.14 to .62) to 1.46 (95% CI, .72-2.20). Measures of activity effect sizes were from .04 (95% CI, -.35 to .44) to .93 (95% CI, -.39 to 2.25); for Motor Activity Log, from .07 (95% CI, -.66 to .80) to 1.24 (95% CI, .47-2.01); and for participation, from -3.32 (95% CI, -4.52 to 2.11) to 1.78 (95% CI, 0-3.56). CONCLUSIONS: AT treatments appear to give modest additional benefit when compared with usual care or in addition to usual care. This is most apparent for subjects early poststroke with 2 caveats: high-intensity constraint-induced movement therapy and electrical stimulation exclusively to the shoulder appear detrimental. The heterogeneity of treatment parameters and population characteristics precludes specific recommendations. Research would benefit from modeling studies to explicitly define criteria of population, intervention, comparator, and outcomes for effective treatments before the development of efficiently integrated care pathways.

Source: PubMed

Preferred by: Ian Swain

Assistive Technologies: Can They Contribute to Rehabilitation of the Upper Limb After Stroke?

Authors: Farmer, S.E., Durairaj, V., Swain, I. and Pandyan, D.

Journal: ARCHIVES OF PHYSICAL MEDICINE AND REHABILITATION

Volume: 95

Issue: 5

Pages: 968-985

eISSN: 1532-821X

ISSN: 0003-9993

DOI: 10.1016/j.apmr.2013.12.020

Source: Web of Science (Lite)

Assistive technologies: can they contribute to rehabilitation of the upper limb after stroke?

Authors: Farmer, S.E., Durairaj, V., Swain, I. and Pandyan, A.D.

Journal: Archives of physical medicine and rehabilitation

Volume: 95

Issue: 5

Pages: 968-985

eISSN: 1532-821X

ISSN: 0003-9993

DOI: 10.1016/j.apmr.2013.12.020

Abstract:

Objective

To systematically identify, review, and explore the evidence for use of assistive technologies (ATs) in poststroke upper limb rehabilitation.

Data sources

AMED, CINAHL, Cochrane Library, Compendex, CSA Illumina, EMBASE, MEDLINE, PEDro, PyscINFO, and Web of Science were last searched in September 2011.

Study selection

Two independent researchers screened for inclusion criteria (adult poststroke subjects, upper limb rehabilitation with an AT). The risk of bias was assessed. Randomized controlled trials of poststroke subjects with baseline equivalence as assessed by blinded assessors were selected for data extraction.

Data extraction

Details of subjects, experimental and control treatments, and all outcomes were recorded in a spreadsheet.

Data synthesis

These data were used to calculate effect sizes for all outcome measures. Impairment measures ranged from -.39 (95% confidence interval [CI], -1.14 to .62) to 1.46 (95% CI, .72-2.20). Measures of activity effect sizes were from .04 (95% CI, -.35 to .44) to .93 (95% CI, -.39 to 2.25); for Motor Activity Log, from .07 (95% CI, -.66 to .80) to 1.24 (95% CI, .47-2.01); and for participation, from -3.32 (95% CI, -4.52 to 2.11) to 1.78 (95% CI, 0-3.56).

Conclusions

AT treatments appear to give modest additional benefit when compared with usual care or in addition to usual care. This is most apparent for subjects early poststroke with 2 caveats: high-intensity constraint-induced movement therapy and electrical stimulation exclusively to the shoulder appear detrimental. The heterogeneity of treatment parameters and population characteristics precludes specific recommendations. Research would benefit from modeling studies to explicitly define criteria of population, intervention, comparator, and outcomes for effective treatments before the development of efficiently integrated care pathways.

Source: Europe PubMed Central