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Microprocessor-based ambulatory activity monitoring in stroke patients


Medicine & Science in Sports & Exercise: March 2002 - Volume 34 - Issue 3 - p 394-399
CLINICAL SCIENCES: Clinical Investigations

MACKO, R. F., E. HAEUBER, M. SHAUGHNESSY, K. L. COLEMAN, D. A. BOONE, G. V. SMITH, and K. H. SILVER. Microprocessor-based ambulatory activity monitoring in stroke patients. Med. Sci. Sports Exerc., Vol. 34, No. 3, pp. 394–399, 2002.

Purpose Recovery of ambulatory function after stroke is routinely assessed using standardized subject- or observer-rated instruments that do not directly measure ambulatory activities in the home-community setting. Accuracy of conventional pedometers in stroke patients is not established, limiting their application in mobility outcomes monitoring. This study investigates the accuracy and reliability of a mechanical pedometer versus microprocessor-based step activity monitoring (SAM) in gait-impaired hemiparetic stroke patients.

Methods Accuracy and test-retest reliability of ankle-worn SAM and belt-worn pedometer were tested directly against hand tallied stride counts and cadence during a battery of timed walks in 16 chronic hemiparetic stroke patients. Patients performed replicate 1-min floor walks at self-selected and fastest comfortable paces, and two 6-min walks on separate days.

Results SAM cadence and total stride counts are more accurate than pedometers during 1-min walks at self-selected (99 ± 1 vs 87 ± 11.3%, mean ± SD, P < 0.01); fast pace (98 ± 2.3% vs 85 ± 15%, P < 0.01); and repeated 6-min walks performed on separate days (99 ± 1% vs 89 ± 12%, P < 0.01). Although SAM is highly reliable (r = 0.97, P < 0.0001) and accurate in all patients under every walking condition tested, the mechanical pedometer demonstrates this high level of accuracy in only half of stroke patients and has poor test-retest reliability (r = 0.64, P < 0.05).

Conclusion SAM, but not the conventional pedometer, provides accurate and reliable measures of cadence and total stride counts in hemiparetic stroke patients. Portable microprocessor-based gait monitoring offers potential to quantitatively measure home-community-based ambulatory activity levels in this population.

Baltimore Veterans Affairs Medical Center Geriatrics Research, Education, and Clinical Center, Baltimore, MD; The University of Maryland School of Medicine Division of Gerontology, Departments of Neurology, Physical Therapy, and School of Nursing, Baltimore, MD; The Prosthetics Research Study, Seattle, WA; and Departments of Orthopedics and Rehabilitation, University of Washington, Seattle, WA

Submitted for publication December 2000.

Accepted for publication June 2001.

Each year about 750,000 Americans suffer a stroke, two thirds of which are left with residual neurological deficits that persistently impair function (10,34). In particular, hemiparesis is the most common motor deficit persistently impairing function, with nearly half of patients still affected >6 months after the index stroke event (32). A major rehabilitation goal for many stroke patients is recovery of functional mobility with return to home and community-based ambulatory activity (33). However, no valid and reliable methods for quantifying ambulatory activity levels are established in the gait-impaired stroke population. Standardized and well-validated instruments indexing global disability, mobility, and basic activities of daily living (ADL) are routinely employed to assess rehabilitation outcomes after stroke (3,20,23). Further information regarding performance of complex activities is derived from instrumental ADL scales, as jointly recommended for the comprehensive evaluation of stroke outcomes by consensus (11,14,28). Yet, these instruments lack sensitivity in mild-moderate severity stroke, which constitute a majority of stroke survivors (5,6,16). Furthermore, neither existing stroke rehabilitation outcomes instruments nor laboratory-based functional mobility tests directly measure the intensity or duration of home-community-based ambulatory activities.

A variety of portable monitoring devices including pedometers and accelerometers have been applied to measure ambulatory activity levels and estimate energy expenditure in healthy individuals and selected nonneurological disability conditions (1,15,17,30–31). However, the accuracy of these devices may vary considerably depending on such factors as walking velocity, amount of soft tissue at the attachment location, and altered gait biomechanics (17). The marked heterogeneity in gait patterning, ground reaction force asymmetry, and slow gait velocities, along with utilization of a variety of assistive devices and lower extremity orthoses that also alter gait biomechanics, render conventional pedometer- or accelerometer-derived recordings unreliable in the stroke population. Hence, portable monitoring of ambulatory function in gait-impaired stroke patients presents formidable technical difficulties. No prior studies, to our knowledge, have established the accuracy and reliability of continuous portable ambulatory activity monitoring devices in hemiparetic stroke patients.

The step activity monitor (SAM, Fig. 1) is a pager-sized stride counter utilizing a microprocessor linked custom accelerometer with adjustable filtering thresholds for motion and cadence parameters (Patent: Gait Activity Monitor, Prosthetics Research Study, U.S. Patent No. 5, 1996) (2). SAM is worn on one ankle; therefore, it records one complete gait cycle as a stride count. Adjustable calibration parameters enable this time-integrated programmable monitor to recognize basic stance and swing components. This function accommodates numerous gait styles in humans and animals for continuous field recording of cadence and total strides taken over prolonged monitoring of user-defined recording epochs. This study investigates the accuracy and reliability of the SAM and conventional belt-worn mechanical pedometers in measuring cadence and stride count in stroke patients with a broad spectrum of gait deficit severity and ambulatory adaptive device requirements.



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Patients >55 yr of age with remote ischemic stroke (>6 months) were recruited from The Baltimore Veterans Affairs Medical Center and The University of Maryland Medical System. All had completed conventional physical therapy and were left with residual hemiparetic gait deficits with some preserved capacity for ambulation, albeit with an adaptive device (e.g., walker or cane) and/or standby aid. Chronic hemiparetic stroke patients were selected in order to optimize test-retest reliability studies within a heterogeneous gait impaired but neurologically stable stroke cohort. Baseline evaluations included a medical history and physical examination, a Mini-Mental Status Exam to screen for dementia (score < 22), and a customized treadmill stress test (19). Exclusion criterion included congestive heart failure (NYHA Class II), unstable angina, dementia, global or major receptive aphasia, peripheral vascular disease, or other major medical conditions limiting ambulatory function. The Baltimore Veterans Administration Medical Center and The University of Maryland Institutional Review Board approved the study and all patients provided written informed consent.

Accuracy and reliability of the SAM and pedometer were evaluated against visually counted strides recorded using a hand tally counter during a battery of timed walks. Because the SAM counts strides, each of which constitutes two steps, and the conventional pedometer counts individual steps, pedometer counts were halved to allow for comparison with visually counted strides. Two 6-min floor walks were performed on separate days with patients instructed to walk at self-selected pace using the same adaptive device and/or orthosis as normally used within their place of residence. Replicate sets of two 1-min floor walks at self-selected and fastest comfortable paces were performed on a separate day. Mean floor walking velocities (m·s−1) at self-selected and fastest pace were calculated from the repeated 1-min timed walks. All timed floor walk tests were conducted on the indoor track (27 laps/mile, nonbanked) of the Baltimore Veterans Affairs Medical Center Senior Exercise Rehabilitation Center. Interval rests were provided between each walk to minimize the potential confounding effects of fatigue on gait patterning during repeated walk testing. The belt-worn pedometer was attached at the nonparetic hip at the midline of the thigh and calibrated against 10 strides, according to protocol (Elexis Trainer, Model #FM-180, International Microtech, Miami, FL). SAM was attached using two elastic straps with adjustable Velcro closure to the nonparetic ankle above the medial malleolus if the left leg and above the lateral malleolus if the right leg, according to manufacturers recommendations to maximize accuracy. Hence, the SAM was attached in hemiparetic patients to record strides based on the acceleration curves of the nonparetic leg. Those individuals with bilateral paretic gait deficits had the SAM attached at the ankle of the less affected leg, based on the clinical evaluation of gait and neurological examination. One-minute recording epochs were used during the 6-min timed walks and 12-s recording epochs during the 1-min walks.

Standardized initial sensitivity settings of 80 for cadence and manufacturer recommended motion settings for slow walkers were employed based on our preliminary experience in hemiparetic stroke patients. This testing strategy was selected to determine whether one generic set of SAM sensitivity settings is accurate for most or all stroke patients tested at different walking paces across short distances, as used in the home (e.g., 1-min walks) and across longer distances as required for community-based ambulatory activities (e.g., 6-min walks). If SAM demonstrated <90% accuracy against visual counts during timed walk testing under any conditions, we further adjusted the cadence sensitivity parameter and retested. Data from SAM was downloaded using an infrared docking port with customized software (Prosthetics Research Study) yielding stride counts and cadence for each timed walk. Accuracy (%) of SAM and pedometer recordings compared with hand-tallied visual counts for measures of total strides taken and cadence was determined for all timed walks. Intraclass correlation coefficients calculated using SAS were used to analyze the test-retest reliability of pedometer and SAM total stride recordings during 6-min walks repeated on separate days.

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We tested 16 patients with mean age 67 ± 7 yr (mean ± SD) including eight with left, six with right hemispheric infarctions, and two with bilateral paretic gait after vertebral-basilar territory stroke. One patient with left hemiparetic gait after a right subcortical lacunar infarction had ipsilateral ataxia due to a later left sided cerebellar infarction. A second patient with brainstem stroke also had ataxic gait. All patients tolerated the SAM securely attached to the ankle without complication or discomfort throughout the testing. The mean latency since stroke was 68.2 months (range 7–311 months). Five patients had mild deficits requiring no assistive device during routine ambulatory activities around the home, whereas eight used a single-point cane and three had greater deficit severity requiring a walker (N = 2) or quad cane (N = 1). Six patients utilized an ankle-foot orthosis during testing. The mean distance traversed during 6-min walks was 264 ± 116 m (range 43–497 m), and the mean self-selected floor walking velocity calculated from 1-min timed walks was 0.74 ± 0.29 m·s−1 and ranged from 0.11–0.97 m·s−1. These timed walk performances constitute a broad spectrum of gait deficit severity, with values ranging from those reported for hemiparetic patients with extremely limited ambulatory function to those typically found in normal elderly controls (19).

Accuracy of SAM- and pedometer-derived cadence measures as compared with direct visual counts during 1-min timed walks at self-selected and fastest comfortable paces is shown in Table 1. SAM-derived cadence values are significantly more accurate than pedometer recordings at both self-selected (N = 16, 98.7 ± 1.2% vs 87.2 ± 11.3%, P < 0.01) and fastest comfortable floor walking paces (97.8 ± 2.3% vs 84.8 ± 14.8%, P < 0.01). Likewise, SAM-derived total stride counts demonstrate greater accuracy than pedometer recordings during 6-min walks (98.7 ± 1.2% vs 89.0 ± 11.93%, P < 0.01). The SAM-derived total stride counts during 6-min walk tests performed on separate days remained a mean of 98% accurate compared with hand-tallied counts (Table 2). Likewise, the test-retest reliability for total stride counts measured during 6-min walks on separate days by SAM (r = 0.975, P < 0.0001) was essentially the same as that for direct hand-tallied visual counts (r = 0.977, P < 0.0001). Mechanical pedometer reliability during replicate 6-min walks was poor (r = 0.64, P < 0.05), indicating that measurements using this instrument account for only 40% of the variance in total stride counts recorded on separate days in stroke patients.

Table 1

Table 1

Table 2

Table 2

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).

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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.

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