Quantified measurement of activity provides insight into motor function and recovery in neurological disease

Author(s): Busse ME, Pearson OR, Van Deursen R, Wiles CM

Abstract

Background:A direct quantitative measurement of locomotor activity in an individual's own environment over an extended period may help in evaluating the impact of impairments in neurological disorders.

Objective:To investigate the reliability and validity of activity monitoring in neurological patients and healthy subjects.

Methods:Initial reliability studies were completed on 10 healthy subjects and 10 mobility restricted neurological patients. Validity was investigated using 7 days of ambulatory monitoring with the Step Watch( step activity monitor, laboratory based measures of gait and the Rivermead Mobility Index (RMI) in 10 patients with multiple sclerosis, 10 with Parkinson's disease, and 10 with a primary muscle disorder. Additionally, 30 healthy subjects participated in the study. Two clinical illustrations of ambulatory monitoring are provided.

Results:The mean (range) right step count of 7 days of monitoring in both healthy and neurological patients proved a reliable measure of activity (intra-class correlations 0.89 and 0.86 respectively). The 7 day mean (range) right step count was 5951 (2886-9955) in healthy subjects, 3818 (1611-5391) in patients with Parkinson's disease, 3003 (716-5302) in those with muscular disorders, and 2985 (689-5340) in those with multiple sclerosis. A moderate correlation was noted between 7 day mean step count and gait speed (r = 0.45, p = 0.01) in the grouped neurological patients but not the RMI (r(s) = 0.3, p = 0.11).

Conclusion:Ambulatory monitoring provides a reliable and valid measure of activity levels. Neurological patients, living independently, demonstrate lower activity levels than healthy matched controls. Ambulatory monitoring as an outcome measure has potential for improving the evaluation of ambulation and providing insight into participation.

Similar Articles

Prediction of adherence and control in diabetes

Author(s): Kavanagh DJ, Gooley S, Wilson PH

Correlates of adults' participation in physical activity: review and update

Author(s): Trost SG, Owen N, Bauman AE, Sallis JF, Brown W

Physical activity patterns in a diverse population of women

Author(s): Sternfeld B, Ainsworth BE, Quesenberry CP

The Generalized Self-Efficacy Scale in people with arthritis

Author(s): Barlow JH, Williams B, Wright C

Self-efficacy predicting outcome among fibromyalgia subjects

Author(s): Buckelew SP, Huyser B, Hewett JE, Parker JC, Johnson JC, et al.

Physical activity and multiple sclerosis: a meta-analysis

Author(s): Motl RW, McAuley E, Snook EM

Uhthoff and his symptom

Author(s): Selhorst JB, Saul RF

Resistance training improves strength and functional capacity in persons with multiple sclerosis

Author(s): White LJ, McCoy SC, Castellano V, Gutierrez G, Stevens JE, et al.

A review about the impact of multiple sclerosis on health-related quality of life

Author(s): Benito-León J, Morales JM, Rivera-Navarro J, Mitchell A

Exploring differences between subgroups of multiple sclerosis patients in health-related quality of life

Author(s): Pfennings L, Cohen L, Adèr H, Polman C, Lankhorst G, et al.

Randomized controlled trial of yoga and exercise in multiple sclerosis

Author(s): Oken BS, Kishiyama S, Zajdel D, Bourdette D, Carlsen J, et al.

Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria

Author(s): Polman CH, Reingold SC, Banwell B, Clanet M, Cohen JA, et al.

The Multiple Sclerosis Impact Scale (MSIS-29): a new patient-based outcome measure

Author(s): Hobart J, Lamping D, Fitzpatrick R, Riazi A, Thompson A

Multiple Sclerosis Impact Scale (MSIS-29): reliability and validity in hospital based samples

Author(s): Riazi A, Hobart JC, Lamping DL, Fitzpatrick R, Thompson AJ

Resistance training improves gait kinematics in persons with multiple sclerosis

Author(s): Gutierrez GM, Chow JW, Tillman MD, McCoy SC, Castellano V, et al.