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RehabMeasures Instrument

Step Activity Monitor

Last Updated

Purpose

Records the number of steps in a time interval over extended periods of monitoring.

Acronym SAM

Cost

Not Free

Cost Description

Pricing provided by company upon request.

Diagnosis/Conditions

  • Brain Injury Recovery
  • Multiple Sclerosis
  • Parkinson's Disease & Movement Disorders
  • Stroke Recovery

Key Descriptions

  • Requires programming by entering the subject’s height and answering four questions about gait for determining cadence and dynamic step.
  • Worn on the ankle, steps usually recorded for one minute, time sequencing allows patterns of activity and rest to be visualized in detail.
  • Analysis of the recording involves breaking down of the time spent and the steps taken at low, moderate and high activities, and activity/ time analysis to find the most active 1, 5, 20, 30 and 60 minute periods during the day.
  • Reports the average step count.

Number of Items

1

Equipment Required

  • SAM
  • Step Watch USB dock
  • Step Watch analysis software
  • Computer with Windows (98,2000, ME, XP, NT) or Mac (OSX)

Time to Administer

2 months

Continuous step monitoring during the day, step recorded at short adjustable time intervals usually one minute for a period ranging from 1-2 weeks to 2 months

Required Training

Reading an Article/Manual

Instrument Reviewers

Initially reviewed by Shweta Subramani in 10/2013.

ICF Domain

Activity

Considerations

  • It is easy to use and the most accurate ambulatory activity monitor (Boone and Coleman, 2006).
  • Requires programming for administration and system requirements for analysis The case is contoured to fit comfortably against the leg. It is securely attached to the ankle by an elastic strap. The straps can also be removed and the monitor can be worn in a soft cloth sleeve at the ankle.

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Spinal Injuries

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Standard Error of Measurement (SEM)

Incomplete Spinal Cord Injury:

(Bowden and Behrman, 2007; = 11; during 6 minute walk test (6MWT) and 10 meter walk test (10 MWT), mean age = 24.0 years, mean 19.7 months post injury) 

  • SEM during 6MWT = 6.0 steps 
  • SEM during 10MWT =  0.8 steps

Minimal Detectable Change (MDC)

Incomplete Spinal Cord Injury:

(Bowden and Behrman, 2007) 

  • MDC for entire group during 6MWT = 16.6
  • MDC for entire group during 10 MWT = 2.22

Test/Retest Reliability

Incomplete Spinal Cord Injury:

(Bowden and Behrman, 2007) 

  • Excellent test-retest reliability (ICC= 0.97-0.99)

Content Validity

  • It was designed to measure step activity in people with lower limb amputation, and then it was in other populations and found to be reliable in assessing gait functionality (Boone and Coleman, 2006)

Stroke

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Test/Retest Reliability

 

Chronic stroke:

(Mudge and Stott, 2008; n = 40, mean age = 69.2(12.6) years, mean years post stroke = 5.1) 

  • Excellen test-retest reliability (ICC = 0.930-0.989) during 3 day monitoring 
  • Good test-retest reliability (ICC = 0.830-0.950) during 1 day monitoring 

 

Stroke:

(Haeuber et al, 2004; = 17, mean age = 65 (6) years, mean latency since stroke = 41.6 months) 

  • Excellent test-retest reliability (r = 0.96, p < 0.001) across separate monitoring periods

Criterion Validity (Predictive/Concurrent)

Concurrent validity:

Stroke:

(Mudge et al, 2007; = 25, mean age = 69 years, 6 months post stroke)

  • Excellent relationship with 3 dimensional gait analysis(3DGA) (r = 0.959 for non-paretic limb, r= 0.896 for paretic limb) 
  • Excellent relationship with foot switches (r = 0.999 for non-paretic limb, r = 0.963 for paretic limb)

Mixed Populations

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Criterion Validity (Predictive/Concurrent)

Concurrent validity:

Parkinson’s Disease(PD) and Multiple sclerosis(MS):

Schmidt et al, 2011; n = 20, while ambulating 15m) 

  • Excellent relationship with Gait mat II(GM II) during 15 m walking (r = 0.99 in MS and r = 1.0 in PD)

Non-Specific Patient Population

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Test/Retest Reliability

Healthy adults:

(Mudge et al, 2010; = 30, mean age = 27.7(8.9) years, without any existing co-morbidity) 

  • Good test-retest reliability (ICC=0.44-0.91)

Floor/Ceiling Effects

Diabetes:

  • Floor and ceiling effects eliminated (Smith et al, 2004)

Bibliography

Boone, D. A. and Coleman, K. L. (2006). "Use of a step activity monitor in determining outcomes." JPO: Journal of Prosthetics and Orthotics 18(6): P86-P92. 

Bowden, M. G. and Behrman, A. L. (2007). "Step Activity Monitor: accuracy and test-retest reliability in persons with incomplete spinal cord injury." J Rehabil Res Dev 44(3): 355-362. 

Cavanaugh, J. T., Coleman, K. L., et al. (2007). "Using Step Activity Monitoring to Characterize Ambulatory Activity in Community‐Dwelling Older Adults." Journal of the American Geriatrics Society 55(1): 120-124. 

Haeuber, E., Shaughnessy, M., et al. (2004). "Accelerometer monitoring of home- and community-based ambulatory activity after stroke." Arch Phys Med Rehabil 85(12): 1997-2001. 

McDonald, C. M., Widman, L., et al. (2005). "Utility of a step activity monitor for the measurement of daily ambulatory activity in children." Arch Phys Med Rehabil 86(4): 793-801. 

Mudge, S. and Stott, N. S. (2008). "Test--retest reliability of the StepWatch Activity Monitor outputs in individuals with chronic stroke." Clin Rehabil 22(10-11): 871-877. 

Mudge, S., Stott, N. S., et al. (2007). "Criterion validity of the StepWatch Activity Monitor as a measure of walking activity in patients after stroke." Archives of physical medicine and rehabilitation 88(12): 1710-1715. 

Mudge, S., Taylor, D., et al. (2010). "Test-retest reliability of the StepWatch Activity Monitor outputs in healthy adults." J Phys Act Health 7(5): 671-676.  

Schmidt, A. L., Pennypacker, M. L., et al. (2011). "Validity of the StepWatch Step Activity Monitor: preliminary findings for use in persons with Parkinson disease and multiple sclerosis." Journal of Geriatric Physical Therapy 34(1): 41-45. 

Smith, D. G., Domholdt, E., et al. (2004). "Ambulatory activity in men with diabetes: Relationship between self-reported and real-world performance-based measures." Journal of rehabilitation research and development 41(4): 571-580.