The preselected cadence and motion sensitivity settings (cadence = 80, motion = 12) for SAM proved >97% accurate in all cases for 1-min walks at self-selected pace but undercounted strides by 17% in one patient with cadence values >65 strides·min−1 at fastest pace. This was corrected to 94% accuracy compared with visual counts by a single adjustment, decreasing the value of the SAM cadence sensitivity setting (cadence = 70). The generic initial sensitivity settings were >97% accurate in all but one patient during repeated 6-min walks. In the patient with the lowest cadence values (30 strides·min−1), SAM overcounted strides by 22%. This was corrected with a single adjustment by increasing the value of the cadence sensitivity setting (cadence = 90), improving accuracy to 97% in this patient. Hence, the initial preselected SAM sensitivity settings proved highly accurate in all stroke patients with cadence values ranging from 32 to 65 strides·min−1. Further adjustment of the cadence sensitivity achieved high accuracy, as reported, in those few patients whose floor walking cadence values fell outside these broad cadence parameters. By contrast, the pedometer counts were highly accurate (>94%) in only half of stroke patients during 6-min walks and in only 56% of patients during 1-min walks at either pace. Although the pedometer tended to perform most accurately in those patients with higher cadence values during 1-min walks (Table 1), this pattern was not consistent. There were no apparent clinical predictors based on gait deficit features, assistive device, or orthoses usage that consistently predicted pedometer accuracy in these stroke patients. Further, the pedometer failed to record, or grossly miscounted steps in a substantial proportion (5/32) of 6-min timed walks, despite proper placement and calibration over 10 paces immediately preceding each walking test (Table 2).
Ambulatory activity monitoring using the microprocessor-based SAM is highly reliable and accurate in all hemiparetic stroke patients tested. SAM accurately and reliably measures stride counts and cadence during 1-min walks, simulating brief distance ambulatory ADLs within the home and during 6-min walks that may better represent a minimal distance required for some basic ambulatory functions outside the home, such as traversing a parking lot. Accuracy is maintained at both self-selected and fastest comfortable speeds within individuals, and across a broad range of gait deficit severity ranging from mild hemiparesis requiring no cane to more severe deficits with patients utilizing a quad cane or walker during testing. These findings demonstrate that microprocessor-based personal status monitoring is a valid and reliable method for quantifying ambulatory activity in hemiparetic stroke patients across a broad range of gait deficit categories.
Numerous noncalorimetric methodologies have been applied to assess physical activity levels in healthy and selected disabled populations. These include activity recall questionnaires and a variety of portable monitoring devices, which either count strides or provide accelerometer-derived estimates of leisure time activity (1,15,17,30–31). Activity recall questionnaires are limited by recall bias and do not provide a quantitative measure of ambulatory activity (1,15,17,30–31). Accelerometers provide sums or integrated measures of movement yielding estimates of leisure time energy expenditure based on normative algorithms for rates of caloric utilization during physical activity in nondisabled individuals (15). Their accuracy may differ substantially in older adults as a function of exercise mode and intensity when compared directly with measures of oxygen consumption (7). Moreover, energy costs of hemiparetic gait varies considerably between stroke patients and are generally 1.5- to 2-fold higher than normal controls at any given gait velocity (9). Hence, the interpretation of conventional accelerometer-derived estimates of free-living energy expenditure, which do not define an ambulatory unit of measurement, remains uncertain in the hemiparetic stroke population.
Pedometers that register foot impacts have been utilized extensively to measure physical activity in young and older healthy populations (15,29). Yet, conventional pedometers vary in accuracy under different walking speeds and test conditions, even in normal individuals (17). Though not previously tested in stroke patients, their reliability in gait-impaired subjects is questionable (2,17,30). Our findings confirm that conventional mechanical pedometers have limited accuracy and poor test-retest reliability in hemiparetic stroke patients. Microswitch stride counters embedded within a prosthetic foot have been developed to address these limitations in amputees (4,12). In hemiparetic stroke patients, Roth et al. (24) measured temporal gait parameters by using bilateral heel and anterior located footswitches attached to a belt worn microprocessor, with a third-inactive switch under each arch to prevent pronation due to the thickness of the active switches. Although these innovative designs have proven accurate, they are impractical for continuous outpatient ambulatory monitoring in stroke patients. The ankle-worn microprocessor-based stride activity monitors used in the present study afford continuous direct measurement of total strides and cadence enabling ambulatory time-intensity activity profile determinations in community-dwelling stroke patients.
This study is limited by the small sample size, inclusion of stroke patients with only chronic neurological deficits and predominantly hemiparetic gait deviation patterns, as well as the brevity of the monitoring epochs. Most of our studies were conducted using SAM attached to the ankle of the unaffected leg in hemiparetic patients. Our study included only two patients with bilateral paretic gait disturbance and two with cerebellar ataxia. Although SAM proved equally efficacious in these patients, this sample size is inadequate to establish accuracy across these neurological deficit categories. Monitoring efficacy was evaluated only during brief timed walks conducted in the setting of an exercise rehabilitation center, not field tested in patients’ homes or prospectively across the subacute stroke rehabilitation period during which substantial recovery in gait function may occur (5,16). However, SAM is programmable for continuous monitoring across prolonged monitoring periods, and the adjustable sensitivity settings should enable customization to account for any changes in gait patterning, which may affect accuracy during stroke recovery within subjects. Further studies are planned to determine the efficacy of outpatient monitoring and utility of ambulatory activity levels as an outcomes instrument after stroke.
In summary, we demonstrate portable microprocessor-based ambulatory activity monitoring is accurate and reliable in hemiparetic stroke patients across a broad range of gait deficit severity. The SAM provides highly accurate, time-integrated stride counts and cadence data for all patients under slow and faster walking velocities, across short and longer distances, regardless of the use of conventional assistive devices and orthoses. The clinical implications are that such monitors may provide a quantitative means to assess minute-by-minute home- and community-based ambulatory activity intensity profiles consistent with emerging WHO Disability and Stroke Outcomes Classification initiatives (14,33). The American Heart Association recommends regular aerobic exercise for health promotion and disease prevention, including after myocardial infarction where this lifestyle modification improves survival (8). Physical inactivity is also an important predictor for increased risk of stroke (18,27). Hemiparetic stroke patients are profoundly physically deconditioned (13,25), remain at high risk for recurrent stroke and cardiac death (26), and most assume a sedentary lifestyle upon completing conventional rehabilitation. To date, there are no empiric guidelines to promote therapeutic exercise in chronically disabled stroke patients and no established methodologies available for clinicians to measure free living physical activity in this high cardiovascular disease risk population. Microprocessor-based ambulatory activity monitoring may provide a practical instrument to help assess activity levels in stroke patients to determine whether they are in compliance with public health recommendations for promoting regular physical activity to improve cardiovascular health and fitness for all Americans (21–22,24).
Our appreciation is extended to the participants.
This study was supported in part by The Baltimore Veterans Administration Geriatrics Research, Education, and Clinical Center, a Veterans Affairs Medical Center Career Development Award, and a grant from The National Institute on Aging to Dr. Macko (R29 AG14487-01), Veterans Affairs Medical Center Merit Review Grants to Drs. Macko and Silver, and a Veterans Affairs Postdoctoral Nurse Fellowship Training Award to Dr. Shaughnessy.
Address for correspondence: Richard Macko, M.D., University of Maryland School of Medicine, Department of Neurology, 22 North Greene St., Baltimore, MD 21201-1595; E-mail richard@grecc. umaryland.edu.
1. Bassey, E. J., H. M. Dallosso, P. H. Fentem, et al. Validation of a simple mechanical accelerometer (pedometer) for the estimation of walking activity. Eur. J. Appl. Physiol. 56: 323–330, 1987.
2. Coleman, K. L., D. G. Smith, D. A. Boone, A. W. Joseph, and M. A. del Aguola. Stride activity monitor
: long-term, continuous recording of ambulatory function. J. Rehabil. Res. Dev. 36: 1–11, 1999.
3. Collen, F. M., D. T. Wade, G. F. Robb, and C. M. Bradshaw. The Rivermead Mobility Index: a further development of the Rivermead Motor Assessment. Int. Disabil. Stud. 13: 50–54, 1991.
4. Day, H. J. B. The assessment and description of amputee activity. Prosthet. Orthot. Int. 5: 23–28, 1981.
5. Dombovy, M. L., J. R. Basford, J. P. Whisnant, and E. J. Bergstralh. Disability and use of rehabilitation services following stroke in Rochester, Minnesota, 1975–1079. Stroke 18: 830–836, 1987.
6. Duncan, P. W., D. Wallace, S. M. Lai, D. Johnson, S. Embretson, and L. J. Laster. The Stroke Impact Scale Version 2.0: evaluation of reliability, validity, and sensitivity to change. Stroke 30: 2131–2140, 1999.
7. Fehling, P. C., D. L. Smith, S. E. Warner, and G. P. Dalsky. Comparison of accelerometers with oxygen consumption in older adults during exercise. Med. Sci. Sports Exerc. 31: 171–175, 1999.
8. Fletcher, G. F., S. N. Blair, J. Blumenthal, et al. Statement on Exercise: benefits and recommendations for physical activity programs for all Americans: a statement for health professionals by the Committee on Exercise and Cardiac Rehabilitation of the Council on Clinical Cardiology, American Heart Association. Circulation 86: 340–344, 1992.
9. Gerston, J., and W. Orr. External work of walking in hemiparetic patients. Scand. J. Rehabil. Med. 3: 85–88, 1971.
10. Gresham, G. E., and T. R. Dawber. Residual disability in survivors of stroke: the Framingham Study. N. Engl. J. Med. 293: 954–956, 1975.
11. Gresham, G. E., P. W. Duncan, W. B. Stason, et al. Post-Stroke Rehabilitation: Clinical Practice Guideline
, No. 16. Rockville, MD: U.S. Department of Health and Human Services. Public Health Service, Agency for Health Care Policy and Research, 1995, AHCPR Publication No. 95–0662.
12. Holden, J., and G. R. Fernie. An assessment of a system to monitor
the activity of patients in a rehabilitation programme. Prosthet. Orthot. Int. 3: 99–102, 1979.
13. Ingles, J. L., G. A. Eskes, and S. J. Phillips. Fatigue after stroke. Arch. Phys. Med. Rehabil. 80: 173–178, 1999.
14. Kelly-Hayes, M., J. T. Robertson, J. P. Broderick, et al. The American Heart Association Stroke Outcome Classification: executive summary. Circulation 97: 2474–2478, 1998.
15. Leon, A. S. Effects of physical activity and fitness in health. In:Assessing Physical Fitness and Physical Activity in Population-Based Surveys
, T. F. Drury (Ed.). Hyattsville, MD: National Center for Health Statistics. 1989, pp. 509–526, DHHS publication no. PHS 89–1253.
16. Jorgensen, H. S., H. Nakayama, H. O. Raaschou, J. Vive-Larsen, M. Strier, and T. S. Olsen. Outcome and time course of recovery in stroke. Part I: outcome. The Copenhagen Stroke Study. Arch Phys. Med. Rehabil. 76: 399–405, 1995.
17. Kochersberger, G., E. McConnell, M. N. Kuchibhatla, and C. Pieper. The reliability, validity, and stability of a measure of physical activity in the elderly. Arch. Phys. Med. Rehabil. 7: 793–795, 1996.
18. Lee, I. M., and R. S. Paffenberger. Physical activity and stroke incidence: the Harvard Alumni Health Study. Stroke 29: 2024–2054, 1998.
19. Macko, R. F., L. I. Katzel, A. Yataco, et al. Low velocity graded treadmill stress testing in hemiparetic stroke patients. Stroke 28: 988–992, 1997.
20. Mahoney, F. I., and D. Barthel. Functional evaluation: the Barthel Index. Md. State Med. J. 14: 56–61, 1965.
21. NIH Consensus Development Panel on Physical Activity and Cardiovascular Health. Physical activity and cardiovascular health. JAMA 276: 241–246, 1996.
22. Pate, R. R., M. Pratt, S. N. Blair, et al. Physical activity and public health: a recommendation from the Centers for Disease Control and Prevention and the American College of Sports Medicine. JAMA 273: 402–407, 1995.
23. Rankin, J. Cerebral vascular accidents in patients over the age of 60. Scott Med. J. 2: 200–215, 1957.
24. Roth, E. J., C. T. Merbitz, J. C. Grip, et al. The timer-logger-communicator gait monitor
: recording temporal gait
parameters using a portable computerized device. Int. Disabil Stud. 12: 10–16, 1990.
25. Ryan, A., L. Dobrovolny, K. Silver, G. Smith, and R. Macko. Cardiovascular fitness after stroke: role of muscle mass and gait
deficit severity. J. Stroke Cerebrovasc. Disord. 9: 1–8, 2000.
26. Sacco, R. L., P. A. Wolf, W. B. Kannel, P. M. McNamara. Survival and recurrence following stroke: the Framingham Study. Stroke 13: 290–295, 1982.
27. Sacco, R. L., R. Gan, B. Boden-Albala, et al. Leisure-time physical activity and ischemic stroke risk: the Northern Manhattan Stroke Study. Stroke 29: 380–387, 1998.
28. Schuling, J., R. de Haan, M. Limburg, and K. H. Groenier. The Frenchay Activities Index: assessment of functional status in stroke patients. Stroke 24: 1173–1177, 1993.
29. Sequeira, M. M., M. Rickenbach, V. Weitlisbach, B. Tullen, and Y. Schutz. Physical activity assessment using a pedometer and its comparison with a questionnaire in a large population survey. Am. J. Epidemiol. 142: 989–999, 1995.
30. Sieminski, D. J., L. L. Cowell, P. S. Montgomery, S. B. Pillai, and A. W. Gardner. Physical activity monitoring in patients with peripheral arterial occlusive disease. J. Cardiopulm. Rehabil. 17: 43–47, 1997.
31. Sugimoto, A., Y. Hara, T. W. Findley, and K. Yonemoto. A useful method for measuring daily physical activity by a three-direction monitor
. Scand. J. Rehabil. Med. 29: 37–42, 1997.
32. Wade, D. T., and R. L. Hewer. Functional abilities after stroke: measurement, natural history and prognosis. J. Neurol. Neurosurg. Psychiatry 50: 177–182, 1987.
33. World Health Organization. ICIDH-2: International Classification of Impairments, Activities and Participation: A Manual of Dimensions of Disablement and Functioning. Beta-1: Draft for Field Trials. Geneva: World Health Organization, 1997.
34. Williams, G. R., J. G. Jiang, D. B. Matchar, and G. P. Samsa. Incidence and occurrence of total (first ever and recurrent) stroke. Stroke 30: 2523–2528, 1999.