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Use of step activity monitoring for continuous physical activity assessment in boys with Duchenne muscular dystrophy
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Use of Step Activity Monitoring for Continuous Physical Activity Assessment in Boys With Duchenne Muscular Dystrophy Craig M. McDonald, MD, Lana M. Widman, MS, Denise D. Walsh, MS, Sandra A. Walsh, BS, R. Ted Abresch, MS ABSTRACT. McDonald CM, Widman LM, Walsh DD, Walsh SA, Abresch RT. Use of step activity monitoring for continuous physical activity assessment in boys with Duchenne muscular dystrophy. Arch Phys Med Rehabil 2005;86:802-8. Objectives: To evaluate the StepWatch Activity Monitor (SAM) as a quantitative measure of community ambulation, to investigate activity patterns and heart rate of ambulatory boys with Duchenne muscular dystrophy (DMD), and to correlate the step activity with measures of body composition and strength. Design: Case-control study. Setting: General community and laboratory. Participants: Sixteen ambulatory boys with DMD and 20 male controls (age range, 5–13y). Interventions: Not applicable. Main Outcome Measures: Laboratory determinations of body composition, knee extension strength, and minute-by-minute step rate and heart rate during 3 days of community activity. Results: During the 3 days of activity, DMD subjects, when compared with controls, (1) had significantly more inactive minutes (1096⫾90min/d vs 1028⫾85min/d), (2) took significantly fewer steps and spent fewer minutes at moderate (66⫾31min/d vs 94⫾30min/d) and high step rates (43⫾30min/d vs 72⫾38min/d), (3) had higher resting heart rate (110⫾12 beats/min vs 94⫾7 beats/min) and lower increase in heart rate with increased step rate, and (4) had lower maximum heart rates (164⫾24 beats/min vs 208⫾16 beats/min). Percentage of body fat and knee extension strength correlated with total step activity in the DMD group but not in the control group. Conclusions: Step-rate monitoring with the SAM provides useful outcome measures with which to evaluate the activity of ambulatory boys with DMD. Their heart rate did not increase with activity to the same degree as observed in the control group. Key Words: Ambulation disorders, neurologic; Body composition; Monitoring, ambulatory; Muscular dystrophy, Duchenne; Rehabilitation. © 2005 by American Congress of Rehabilitation Medicine and the American Academy of Physical Medicine and Rehabilitation
From the Department of Physical Medicine & Rehabilitation, NIDRR Rehabilitation Research and Training Center in Neuromuscular Diseases, University of California, Davis Medical Center, Sacramento, CA. Supported by the National Institute of Disability and Rehabilitation Research (grant no. H133B980008) and the National Institutes of Health (grant no. R01 HD3571401). No commercial party having a direct financial interest in the results of the research supporting this article has or will confer a benefit on the author(s) or on any organization with which the author(s) is/are associated. Reprint requests to Craig M. McDonald, MD, Dept of Physical Medicine & Rehabilitation, University of California, Davis Medical Center, 4860 Y St, Ste 3850, Sacramento, CA 95817, e-mail: [email protected]. 0003-9993/05/8604-9223$30.00/0 doi:10.1016/j.apmr.2004.10.012
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MBULATION IS A MAJOR component of daily physical activity. It is self-regulated in intensity, duration, A and frequency and can be an important indicator of a person’s health and fitness status. Although much effort is made to improve ambulatory function in disabled children with therapy, orthotics, and/or surgery, the degree to which such interventions actually improve ambulation in the real-world community is often unknown. Quantitative measurement of a person’s daily ambulation pattern can provide valuable insight to clinicians and researchers and can serve as an outcome measure in the evaluation of therapeutic interventions in disabled children with functional limitations in gait. This can be especially useful for physicians treating patients with progressive degenerative disorders such as Duchenne muscular dystrophy (DMD), where the goal of pharmacotherapy, physical therapy, or orthopedic surgery may be to maintain or improve ambulatory function. Such measures can also be a way to identify objectively people who are at risk for secondary health conditions that may result from inactivity. This project used the StepWatch Activity Monitor1 (SAM) to record minute-by-minute step activity patterns of young boys diagnosed with DMD and of able-bodied controls. The SAM is a small, lightweight, accurate, unobtrusive device that measures frequency, duration, and intensity of activity.1,2 It has an advantage over pedometers because it records step rates at predetermined intervals that begin as low as 6 seconds. Its advantage over accelerometers is that it accurately records steps taken by subjects with whose gait characteristics vary widely.2 In the past, heart rate has been used as a quantitative measure of physical activity levels. However, physical activity is not the only factor that causes changes in heart rate. Emotional stress, age, body size, and proportion of muscle mass used in cardiorespiratory fitness will influence the heart rate. Because of the deficiencies in use of pedometers, accelerometers, and heart rate monitoring, the SAM may be a more appropriate tool with which to evaluate ambulatory activity in subjects with DMD. Our purpose in this project was (1) to evaluate the utility of the SAM as a quantitative measure of real-world community ambulation and physical activity in children with DMD; (2) to investigate the quantitative activity patterns of young, ambulatory boys with DMD before their full-time wheelchair use to determine the extent to which their activity levels and patterns of activity differ from those of boys without the disease; (3) to assess the relation of the minuteby-minute heart rate to the minute-by-minute step activity in both with DMD and control boys; and (4) to examine whether clinical measures of strength and body composition correlate with the level of total daily step activity. METHODS Participants The subjects were 16 ambulatory boys with DMD, aged 5 to 13 years (mean age, 9.1⫾2.1y), all with their diagnosis con-
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cadence, threshold, and motion of each subject. It was attached to the right ankle just above the lateral malleolus, and the settings were adjusted for each boy’s gait. Subjects were asked to walk first as slowly as they would normally walk and then as fast as they could walk without running while a researcher manually counted the steps taken with the right foot. The data from the SAM were compared with the manually counted tally. When the manual count of steps does not agree with SAMcounted steps, adjustments can be made by changing the settings for sensitivity or cadence in a computer program and by downloading the new data into the SAM. Generally, when manual counts are too high, sensitivity is decreased, and when manual counts are too low, the cadence is decreased. This is a simple process in which information is entered into the computer and uploaded to the SAM before it is given to the user. Heart Rate Monitoring Heart rate was recorded with a Polar Vantage NV heart rate monitord (HRM). The HRM consists of a transmitter strap worn around the chest and a receiver/wristwatch worn on the wrist. The HRM produces a digital text file with 1 value per minute that represents the average heart rate for that minute.
Fig 1. Sample DEXA showing how the body was divided into segmental regions for body composition analysis of specific regions.
firmed by absence of dystrophin on muscle biopsy, and 21 male controls aged 5 to 13 years (mean age, 9.5⫾2.1y). All DMD subjects were referred from the MDA clinic at the University of California (UC) at Davis. Control subjects were recruited from among friends of the boys with DMD or friends of UC Davis employees. All subjects signed consent forms and their parents or guardians signed consent forms that had been approved by the UC Davis Institutional Review Board. Anthropometrics. Height and weight were determined with a standard clinical stadiometer and standard balance scale. Body mass index (BMI) was calculated as body weight (in kilograms) divided by height (in meters squared). Body composition analysis. Body composition was obtained by dual energy x-ray absorptiometry (DEXA) with an Hologic QDR-4500A.a Whole body fat and lean tissue mass were obtained using DEXA whole body scans. The Hologic postprocessing software (Whole Body, version 8.26a:3a) was used to define body segments and measure body fat and lean tissue mass of each segment (fig 1). Strength assessment. Knee extension strength was measured isometrically in newton-meters with a Lido Active MultiJoint Dynamometer with LIDOAct software.b Subjects were positioned with their knee flexed to 45°, as recommended by the manufacturer, and they then performed 3 maximum-effort extensions. The value used for analysis was the peak of the 3 trials. Strength measures were normalized by dividing the strength by either whole body mass or by thigh lean mass (in kilograms). Step Activity Monitoring As described previously,3 the settings of the SAMc were programmed in the laboratory for the expected sensitivity,
Community Activity The SAM and HRM recorded minute-by-minute step rate and heart rate for 3 days (2 weekday/school days, 1 weekend day) for each subject during his normal daily routine. Subjects were instructed to attach the SAM and HRM immediately on waking in the morning and to leave them on until retiring for the night. The times on the HRM and SAM were synchronized to allow combination of the files. Sample graphs showing 1 day of activity are shown in figures 2A through 2D. Each subject kept a log of the time he awoke, the time he went to bed, and his major activities on the days the monitor was worn. The activity levels were defined as zero step rate (inactive), low step rate (LSR) (1–15 steps/min), moderate step rate (MSR) (16 –30 steps/min), and high step rate (HSR) (⬎30 steps/min), as described previously.1,2 The LSR represents activities such as sedentary tasks with short periods of walking. The MSR represents actions such as intermittent walking (⬍2 consecutive minutes) or very slow walking. HSR is the designation used for highly active movements such as running, fast walking, playing sports, or walking continuously for more than 30 seconds. Data Analysis Descriptive data were compiled for height, weight, body fat percentage, thigh lean tissue mass, and isometric leg extension strength. An average value of right and left legs was used for thigh lean mass and isometric leg extension strength. If the data were not homogeneous as determined by the Hartley F test, a log transform was performed on the data before using the Student t test to compare groups. For the 3 days of community activity, the minute-by-minute heart rate during each of the 4 defined step intervals was determined for each boy, and an average value was calculated for both groups at each of the step rates. We used a repeatedmeasures analysis of variance (ANOVA) (split plot in time) to examine the difference between the averaged heart rates at the defined step rates in the DMD and control groups. The dependent variable was heart rate at each step rate (inactive, LSR, MSR, HSR) for the diagnostic groups (control vs DMD). We used Pearson correlation coefficients followed by Bonferroni analyses to compare the association between total steps per day and clinical measures (thigh lean mass, knee Arch Phys Med Rehabil Vol 86, April 2005
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Fig 2. One day of minute-by-minute step rate activity and heart rate data. (A) Minute-by-minute step rate for a 6-year-old control boy. (B) Minute-by-minute heart rate for the same child. (C) Minute-by-minute step rate for a 10-year-old boy with DMD. (D) Minute-by-minute heart rate for the same child.
extension strength, BMI, percentage of body fat) for each group. These correlations with clinical measures were also performed with age. Significance was accepted at a level of P less than .05 for all tests. RESULTS Demographic, Anthropometric, Strength, and Ambulation Measures Although the 2 groups were similar in age, weight, and BMI, the DMD subjects had significantly less lean body mass, less thigh lean mass, and a higher percentage of body fat than the control subjects (table 1). Knee extension strength, knee extension strength per total body mass, and knee extension strength per thigh lean mass were less in the DMD group than in the controls. Knee extension strength correlated positively Arch Phys Med Rehabil Vol 86, April 2005
with thigh lean mass in both groups (control r⫽.83; DMD r⫽.66). SAM Calibration After the final calibration of the SAM, the number of steps it recorded during the slow and fast walk did not differ from the number of steps that were manually counted for any of the subjects. Step Rate During Community Activities The day of the week (weekend vs weekday) had no significant effect on the step data; therefore, the average of the 3 days for each subject was used for comparisons between the 2 groups. There was no difference in the average number of steps taken each day at the LSR (control, 1369⫾85; DMD, 1260⫾103). However, the average number of steps per day at the MSR (control, 2090⫾169;
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Fig 2. (Continued)
DMD, 1500⫾195; P⫽.028) and HSR (control, 2852⫾366; DMD, 1696⫾287; P⫽.022) were significantly higher in the control group than in the DMD group, and the total number of steps per Table 1: Anthropometric and Strength Characteristics Characteristics
Control Group
DMD Group
Age (y) Body mass (kg) BMI (kg/m2) Total fat (kg) Total lean (kg) Body fat (%) Total lean (%) Thigh lean (kg) Thigh lean/body mass (kg/kg) Knee extension strength (Nm) Knee extension strength/body mass (Nm/kg) Knee extension strength/thigh lean mass (Nm/kg)
9.5⫾2.1 32.7⫾9.7 17.0⫾2.3 7.4⫾3.8 24.1⫾7.0 21.9⫾5.7 74.9⫾5.6 2.5⫾0.9 0.08⫾0.01 61.6⫾29.4
9.1⫾2.1 29.4⫾12.1 18.0⫾5.5 9.1⫾8.4 18.9⫾4.0* 27.6⫾11.0 69.9⫾10.6 1.6⫾0.5* 0.06⫾0.01* 9.96⫾7.0*
1.82⫾0.47
0.35⫾0.25*
24.6⫾6.6
6.0⫾3.8*
NOTE. Values are mean ⫾ standard deviation. *DMD significantly different from control (P⬍.05).
day (control, 6311⫾493; DMD, 4456⫾513; P⫽.014) was also higher in the control group (fig 3). There was no difference in the number of hours the 2 groups wore the step monitor each day (control, 779⫾178min; DMD, 856⫾170min) as determined by the data in the diaries. However, the DMD boys spent significantly more total minutes inactive each day (control, 1028⫾19min; DMD, 1095⫾23min; P⫽.028) (fig 4). There was no difference in the time spent at the LSR (control, 245⫾10min; DMD, 235⫾19min), but the control boys spent significantly more time at the MSR (control, 94⫾7min; DMD, 66⫾8min; P⫽.010) and HSR (control, 72⫾9min; DMD, 43⫾7min; P⫽.018). Data were lost with the HRMs for several reasons. The chest strap was either worn incorrectly or not worn at all because of the discomfort it caused. Some subjects ignored instructions not to alter the watch settings, and data were lost due to recording errors. Equal numbers of control boys and boys with DMD were lacking heart rate data and there was no common pattern among the boys with the missing data. Heart Rate During Community Activities Figure 5 shows the mean heart rate recorded from both groups at the defined step rates (inactive, LSR, MSR, HSR). Arch Phys Med Rehabil Vol 86, April 2005
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Fig 3. Average steps per day at each of the step rates during 3 days of community ambulation for control and DMD groups. *Control and DMD groups differed significantly from each other (P<.05). Values are mean ⴞ standard error (SE).
The dependent variable (mean heart rate) was compared at the 4 step rates for each subject in both the control and DMD groups. Repeated-measures ANOVA analysis found no disease effect (P⫽.111) but did find a significant increase in heart rate with an increase in step rate (P⫽.000) and a significant interaction between step rate and disease (P⫽.000). Student t test analysis found that the heart rate of the DMD boys was significantly higher than that of the control boys at rest (P⫽.001) and at the LSR (P⫽.004); at the MSR and the HSR, there was no difference between the 2 groups. The maximum heart rate recorded during the 3 days of community activity was significantly lower in the DMD subjects (164⫾8 beats/min) than in the control subjects (209⫾4 beats/min) (P⫽.000). Over the 3-day period, the average correlation between step rate and heart rate was .477 for control boys but only .295 for the boys with DMD.
Fig 4. Average minutes per day spent at each of the step rates during 3 days of community ambulation for control and DMD groups. *Control and DMD groups differed significantly from each other (P<.05). Values are mean ⴞ SE.
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Fig 5. Mean heart rate for the control and DMD groups at each of the step rates recorded during the 3 days of community ambulation. * Control group differed significantly from DMD group (P<.05). Values are mean ⴞ SE.
Clinical Measurements Correlated With Age and Step Activity To examine whether a relation existed between total steps per day and the physical characteristics examined (strength, body composition), correlation coefficients were calculated (table 2). Total steps per day during the 3-day community activity correlated negatively with BMI (r⫽–.52) and percentage of body fat (r⫽–.67) in the group with DMD but not in the control group. As shown in figure 6, knee extension strength normalized for body mass increased with age in the control group (r⫽.68), but it decreased with age in the DMD group (r⫽–.57). In the control group, knee extension strength and knee extension strength normalized for thigh lean mass significantly increased with age (r⫽.86 and r⫽.49, respectively) but did not show an increase with age in the DMD group. The latter group showed a significant decrease in thigh lean mass with age, whereas the control group did not change significantly with age. DISCUSSION This is the first study to show the usefulness of the SAM for the quantitative evaluation of the physical activity of disabled children in the real-world community environment. The programmability of the SAM allows adjustments that accommodate variations in gait and makes possible an accurate record of each step taken. The results show the ability of the SAM to effectively quantify differences in intensity of activity by measuring the minute-by-minute step rate and to determine differences in the total time spent at specifically defined step rates. The output from the SAM also provides data that allow graphical presentation of the patterns of activity, as shown in figures 2A and 2C. Evaluation of these data allows for characterization of the activities throughout the day or during the recording period. Our results show that young boys with DMD, who are still functional and mobile, have significantly lower levels of higherintensity physical activities (eg, continuous walking, running) and significantly more inactive time each day. Although these children may be able to ambulate short distances in a clinic setting, their ambulatory function in the community may be more impaired than a clinician realizes. Among DMD subjects, there were strong
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STEP ACTIVITY IN DUCHENNE DYSTROPHY, McDonald Table 2: Correlations With Age and Total Steps per Day Age
Total Steps/Day
Characteristic
Controls
DMD
Controls
DMD
Age BMI Body fat (%) Thigh lean/body mass Knee extension strength Knee extension strength/thigh lean Knee extension strength/body mass
— .36 .14 –.23 .86* .49* .68*
— .01 .46 –.60* –.09 –.42 –.57*
–.39 –.16 –.09 –.31 –.20 .11 –.11
–.44 –.52* –.67* .39 –.18 .19 .27
*Significant correlation (Bonferroni, P ⬍ .05).
correlations between the functionally relevant step activity and the clinical measures that are affected by the dystrophic myopathy, including strength and secondary changes in body composition and BMI. These measures appear to be important correlates of ambulatory activity in children with DMD and are easily obtained in a clinical setting. Step activity determinations can monitor changes in functional level, disease progression, and response to therapeutic interventions. Lower-extremity strength values obtained with manual muscle testing and walking speed have been shown to correlate with loss of ambulatory function in DMD.3 The everyday activity of the boys with DMD could be affected by complex factors. Conversely, there was no correlation for the control subjects between any of the strength or body composition measurements and the total average daily steps. In disabled children there may be a critical value where strength loss and change in body composition (lean tissue loss and/or increase in body fat) is associated with a decline in step activity. None of the control subjects had this degree of strength or lean tissue loss, suggesting that their daily activity is more strongly influenced by factors other than strength and body composition parameters— for example, psychosocial or environmental factors, social roles and tasks, or aerobic fitness. In previous studies, HRM was used as a continuous quantitative measure of physical activity in children.4-6 However, HRM can be misleading as a measure of physical activity because heart rate may be influenced by factors other than activity, such as emotion, environmental temperature, body position, fitness level, and type
Fig 6. Change in knee extensor strength per kilogram of body mass with age for the control and DMD groups.
of activity.7 It is particularly difficult to evaluate low level activities through heart rate, because it has little or no change below a threshold heart rate (the flex point).8 This was evident in the boys with DMD who had a relatively poor correlation between heart rate and step activity (r⫽.29), presumably because of their low activity levels. However, the controls had a relatively good correlation between step activity and heart rate (r⫽.48). The lack of correlation between step rate and heart rate in boys with DMD could result from the heart’s inability to respond to increases in activity. As shown in figure 5, the heart rate of the boys with DMD was significantly higher than that of the control subjects at rest and low activity but did not differ at the higher step rates. This higher resting heart rate is not likely to be caused by simple deconditioning, because deconditioned able-bodied people show a large heart rate increase with increased physical activity; in contrast, the DMD boys had a much reduced response to increases in activity. The inability of the heart to respond to such increases may be related to the inappropriate sinus tachycardia observed in DMD.9-11 Sockolov et al11 reported that DMD subjects were unable to substantially increase their cardiac output during submaximal work. The possibility that DMD subjects may exhibit chronotropic incompetence is important in that it has been predictive of all-cause mortality in adults, even after accounting for age, physical fitness, and standard cardiovascular risk factors.12-16 CONCLUSIONS Our study shows that the SAM can be calibrated to accurately record the steps of subjects with DMD, who may have abnormal gait. Because of its ability to record the intensity, duration, and frequency of steps taken during community ambulation, it may be a useful device with which to evaluate therapeutic interventions geared at improving the functional status of children with DMD and other disabilities. We found that the DMD boys were more inactive and spent less time at MSRs and HSRs than did our control group. As a consequence, they took fewer total steps each day and significantly fewer steps at the MSR and HSR. The DMD children also had higher heart rates while inactive and at LSRs. Their heart rate response to increasing step rates was blunted when compared with the heart rate response of the control children. The total steps taken each day correlated with the BMI, percentage of body fat, and knee extensor strength in the DMD group, but they did not correlate in the control group. Step activity monitoring using the SAM appears to be a useful, objective, and unobtrusive method of quantitatively and continuously measuring the overall physical activity level and pattern of ambulatory activity of children with disabilities who have reduced ambulatory function and who may have abnormal gait patterns. Arch Phys Med Rehabil Vol 86, April 2005
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Acknowledgment: We acknowledge the valuable contributions of Kim Coleman, MS, for her technical assistance with the SAM. References 1. Coleman KL, Smith DG, Boone DA, Joseph AW, del Aguila MA. Step Activity Monitor: long-term, continuous recording of ambulatory function. J Rehabil Res Dev 1999;36:8-18. 2. McDonald CM, Widman L, Abresch RT, Walsh SA, Walsh DD. Utility of a step activity monitor for the measurement of daily ambulatory activity in children. Arch Phys Med Rehabil 2005;86: 793-801. 3. McDonald CM, Walsh DD, Widman L, Walsh SA, Coleman K. Use of the Step Activity Monitor for continuous objective threeday physical activity monitoring [abstract]. Dev Med Child Neurol 1999;80(Suppl):36. 4. Meijer GA, Westerterp KR, Koper H, Ten Hoor F. Assessment of energy expenditure by recording heart rate and body acceleration. Med Sci Sports Exerc 1989;21:343-7. 5. Livingstone MB, Robson PJ, Totton M. Energy expenditure by heart rate in children: an evaluation of calibration techniques. Med Sci Sports Exerc 2000;32:1513-9. 6. Maffeis C, Zaffanello M, Pinelli L, Schutz Y. Total energy expenditure and patterns of activity in 8 –10-year-old obese and nonobese children. J Pediatr Gastroenterol Nutr 1996;23:256-61. 7. McArdle WD, Katch FI, Katch VL. Exercise physiology. Baltimore: Williams & Wilkins; 1996. 8. Leonard WR. Measuring human energy expenditure: what have we learned from the flex-heart rate method? Am J Human Biol 2003;15:479-89. 9. D’Orsogna L, O’Shea JP, Miller G. Cardiomyopathy of Duchenne muscular dystrophy. Pediatr Cardiol 1988;9:205-13.
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10. Finsterer J, Stollberger C. The heart in human dystrophinopathies. Cardiology 2003;99:1-19. 11. Sockolov R, Irwin B, Dressendorfer RH, Bernauer EM. Exercise performance in 6-to-11-year-old boys with Duchenne muscular dystrophy. Arch Phys Med Rehabil 1977;58:195-201. 12. Lauer MS, Okin PM, Larson MG, Evans JC, Levy D. Impaired heart rate response to graded exercise. Prognostic implications of chronotropic incompetence in the Framingham Heart Study. Circulation 1996;93:1520-6. 13. Lauer MS, Francis GS, Okin PM, Pashkow FJ, Snader CE, Marwick TH. Impaired chronotropic response to exercise stress testing as a predictor of mortality. JAMA 1999;281:524-9. 14. Lauer MS, Mehta R, Pashkow FJ, Okin PM, Lee K, Marwick TH. Association of chronotropic incompetence with echocardiographic ischemia and prognosis. J Am Coll Cardiol 1998; 32:1280-6. 15. Dresing TJ, Blackstone EH, Pashkow FJ, Snader CE, Marwick TH, Lauer MS. Usefulness of impaired chronotropic response to exercise as a predictor of mortality, independent of the severity of coronary artery disease. Am J Cardiol 2000;86:602-9. 16. Pollock SG, Abbott RD, Boucher CA, Beller GA, Kaul S. Independent and incremental prognostic value of tests performed in hierarchical order to evaluate patients with suspected coronary artery disease. Validation of models based on these tests. Circulation 1992;85:237-48. a. b. c. d.
Suppliers Hologic Inc, 35 Crosby Dr, Bedford, MA 01730. Loredan Biomedical Inc, W Sacramento, CA 95691. Cyma, 8515 35th Ave NE, Seattle, WA 98115. Polar Electro Inc, 34740 Carl Ave, Zephrhills, FL 33541.
Use of Step Activity Monitoring for Continuous Physical Activity Assessment in Boys With Duchenne Muscular Dystrophy Craig M. McDonald, MD, Lana M. Widman, MS, Denise D. Walsh, MS, Sandra A. Walsh, BS, R. Ted Abresch, MS ABSTRACT. McDonald CM, Widman LM, Walsh DD, Walsh SA, Abresch RT. Use of step activity monitoring for continuous physical activity assessment in boys with Duchenne muscular dystrophy. Arch Phys Med Rehabil 2005;86:802-8. Objectives: To evaluate the StepWatch Activity Monitor (SAM) as a quantitative measure of community ambulation, to investigate activity patterns and heart rate of ambulatory boys with Duchenne muscular dystrophy (DMD), and to correlate the step activity with measures of body composition and strength. Design: Case-control study. Setting: General community and laboratory. Participants: Sixteen ambulatory boys with DMD and 20 male controls (age range, 5–13y). Interventions: Not applicable. Main Outcome Measures: Laboratory determinations of body composition, knee extension strength, and minute-by-minute step rate and heart rate during 3 days of community activity. Results: During the 3 days of activity, DMD subjects, when compared with controls, (1) had significantly more inactive minutes (1096⫾90min/d vs 1028⫾85min/d), (2) took significantly fewer steps and spent fewer minutes at moderate (66⫾31min/d vs 94⫾30min/d) and high step rates (43⫾30min/d vs 72⫾38min/d), (3) had higher resting heart rate (110⫾12 beats/min vs 94⫾7 beats/min) and lower increase in heart rate with increased step rate, and (4) had lower maximum heart rates (164⫾24 beats/min vs 208⫾16 beats/min). Percentage of body fat and knee extension strength correlated with total step activity in the DMD group but not in the control group. Conclusions: Step-rate monitoring with the SAM provides useful outcome measures with which to evaluate the activity of ambulatory boys with DMD. Their heart rate did not increase with activity to the same degree as observed in the control group. Key Words: Ambulation disorders, neurologic; Body composition; Monitoring, ambulatory; Muscular dystrophy, Duchenne; Rehabilitation. © 2005 by American Congress of Rehabilitation Medicine and the American Academy of Physical Medicine and Rehabilitation
From the Department of Physical Medicine & Rehabilitation, NIDRR Rehabilitation Research and Training Center in Neuromuscular Diseases, University of California, Davis Medical Center, Sacramento, CA. Supported by the National Institute of Disability and Rehabilitation Research (grant no. H133B980008) and the National Institutes of Health (grant no. R01 HD3571401). No commercial party having a direct financial interest in the results of the research supporting this article has or will confer a benefit on the author(s) or on any organization with which the author(s) is/are associated. Reprint requests to Craig M. McDonald, MD, Dept of Physical Medicine & Rehabilitation, University of California, Davis Medical Center, 4860 Y St, Ste 3850, Sacramento, CA 95817, e-mail: [email protected]. 0003-9993/05/8604-9223$30.00/0 doi:10.1016/j.apmr.2004.10.012
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MBULATION IS A MAJOR component of daily physical activity. It is self-regulated in intensity, duration, A and frequency and can be an important indicator of a person’s health and fitness status. Although much effort is made to improve ambulatory function in disabled children with therapy, orthotics, and/or surgery, the degree to which such interventions actually improve ambulation in the real-world community is often unknown. Quantitative measurement of a person’s daily ambulation pattern can provide valuable insight to clinicians and researchers and can serve as an outcome measure in the evaluation of therapeutic interventions in disabled children with functional limitations in gait. This can be especially useful for physicians treating patients with progressive degenerative disorders such as Duchenne muscular dystrophy (DMD), where the goal of pharmacotherapy, physical therapy, or orthopedic surgery may be to maintain or improve ambulatory function. Such measures can also be a way to identify objectively people who are at risk for secondary health conditions that may result from inactivity. This project used the StepWatch Activity Monitor1 (SAM) to record minute-by-minute step activity patterns of young boys diagnosed with DMD and of able-bodied controls. The SAM is a small, lightweight, accurate, unobtrusive device that measures frequency, duration, and intensity of activity.1,2 It has an advantage over pedometers because it records step rates at predetermined intervals that begin as low as 6 seconds. Its advantage over accelerometers is that it accurately records steps taken by subjects with whose gait characteristics vary widely.2 In the past, heart rate has been used as a quantitative measure of physical activity levels. However, physical activity is not the only factor that causes changes in heart rate. Emotional stress, age, body size, and proportion of muscle mass used in cardiorespiratory fitness will influence the heart rate. Because of the deficiencies in use of pedometers, accelerometers, and heart rate monitoring, the SAM may be a more appropriate tool with which to evaluate ambulatory activity in subjects with DMD. Our purpose in this project was (1) to evaluate the utility of the SAM as a quantitative measure of real-world community ambulation and physical activity in children with DMD; (2) to investigate the quantitative activity patterns of young, ambulatory boys with DMD before their full-time wheelchair use to determine the extent to which their activity levels and patterns of activity differ from those of boys without the disease; (3) to assess the relation of the minuteby-minute heart rate to the minute-by-minute step activity in both with DMD and control boys; and (4) to examine whether clinical measures of strength and body composition correlate with the level of total daily step activity. METHODS Participants The subjects were 16 ambulatory boys with DMD, aged 5 to 13 years (mean age, 9.1⫾2.1y), all with their diagnosis con-
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cadence, threshold, and motion of each subject. It was attached to the right ankle just above the lateral malleolus, and the settings were adjusted for each boy’s gait. Subjects were asked to walk first as slowly as they would normally walk and then as fast as they could walk without running while a researcher manually counted the steps taken with the right foot. The data from the SAM were compared with the manually counted tally. When the manual count of steps does not agree with SAMcounted steps, adjustments can be made by changing the settings for sensitivity or cadence in a computer program and by downloading the new data into the SAM. Generally, when manual counts are too high, sensitivity is decreased, and when manual counts are too low, the cadence is decreased. This is a simple process in which information is entered into the computer and uploaded to the SAM before it is given to the user. Heart Rate Monitoring Heart rate was recorded with a Polar Vantage NV heart rate monitord (HRM). The HRM consists of a transmitter strap worn around the chest and a receiver/wristwatch worn on the wrist. The HRM produces a digital text file with 1 value per minute that represents the average heart rate for that minute.
Fig 1. Sample DEXA showing how the body was divided into segmental regions for body composition analysis of specific regions.
firmed by absence of dystrophin on muscle biopsy, and 21 male controls aged 5 to 13 years (mean age, 9.5⫾2.1y). All DMD subjects were referred from the MDA clinic at the University of California (UC) at Davis. Control subjects were recruited from among friends of the boys with DMD or friends of UC Davis employees. All subjects signed consent forms and their parents or guardians signed consent forms that had been approved by the UC Davis Institutional Review Board. Anthropometrics. Height and weight were determined with a standard clinical stadiometer and standard balance scale. Body mass index (BMI) was calculated as body weight (in kilograms) divided by height (in meters squared). Body composition analysis. Body composition was obtained by dual energy x-ray absorptiometry (DEXA) with an Hologic QDR-4500A.a Whole body fat and lean tissue mass were obtained using DEXA whole body scans. The Hologic postprocessing software (Whole Body, version 8.26a:3a) was used to define body segments and measure body fat and lean tissue mass of each segment (fig 1). Strength assessment. Knee extension strength was measured isometrically in newton-meters with a Lido Active MultiJoint Dynamometer with LIDOAct software.b Subjects were positioned with their knee flexed to 45°, as recommended by the manufacturer, and they then performed 3 maximum-effort extensions. The value used for analysis was the peak of the 3 trials. Strength measures were normalized by dividing the strength by either whole body mass or by thigh lean mass (in kilograms). Step Activity Monitoring As described previously,3 the settings of the SAMc were programmed in the laboratory for the expected sensitivity,
Community Activity The SAM and HRM recorded minute-by-minute step rate and heart rate for 3 days (2 weekday/school days, 1 weekend day) for each subject during his normal daily routine. Subjects were instructed to attach the SAM and HRM immediately on waking in the morning and to leave them on until retiring for the night. The times on the HRM and SAM were synchronized to allow combination of the files. Sample graphs showing 1 day of activity are shown in figures 2A through 2D. Each subject kept a log of the time he awoke, the time he went to bed, and his major activities on the days the monitor was worn. The activity levels were defined as zero step rate (inactive), low step rate (LSR) (1–15 steps/min), moderate step rate (MSR) (16 –30 steps/min), and high step rate (HSR) (⬎30 steps/min), as described previously.1,2 The LSR represents activities such as sedentary tasks with short periods of walking. The MSR represents actions such as intermittent walking (⬍2 consecutive minutes) or very slow walking. HSR is the designation used for highly active movements such as running, fast walking, playing sports, or walking continuously for more than 30 seconds. Data Analysis Descriptive data were compiled for height, weight, body fat percentage, thigh lean tissue mass, and isometric leg extension strength. An average value of right and left legs was used for thigh lean mass and isometric leg extension strength. If the data were not homogeneous as determined by the Hartley F test, a log transform was performed on the data before using the Student t test to compare groups. For the 3 days of community activity, the minute-by-minute heart rate during each of the 4 defined step intervals was determined for each boy, and an average value was calculated for both groups at each of the step rates. We used a repeatedmeasures analysis of variance (ANOVA) (split plot in time) to examine the difference between the averaged heart rates at the defined step rates in the DMD and control groups. The dependent variable was heart rate at each step rate (inactive, LSR, MSR, HSR) for the diagnostic groups (control vs DMD). We used Pearson correlation coefficients followed by Bonferroni analyses to compare the association between total steps per day and clinical measures (thigh lean mass, knee Arch Phys Med Rehabil Vol 86, April 2005
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Fig 2. One day of minute-by-minute step rate activity and heart rate data. (A) Minute-by-minute step rate for a 6-year-old control boy. (B) Minute-by-minute heart rate for the same child. (C) Minute-by-minute step rate for a 10-year-old boy with DMD. (D) Minute-by-minute heart rate for the same child.
extension strength, BMI, percentage of body fat) for each group. These correlations with clinical measures were also performed with age. Significance was accepted at a level of P less than .05 for all tests. RESULTS Demographic, Anthropometric, Strength, and Ambulation Measures Although the 2 groups were similar in age, weight, and BMI, the DMD subjects had significantly less lean body mass, less thigh lean mass, and a higher percentage of body fat than the control subjects (table 1). Knee extension strength, knee extension strength per total body mass, and knee extension strength per thigh lean mass were less in the DMD group than in the controls. Knee extension strength correlated positively Arch Phys Med Rehabil Vol 86, April 2005
with thigh lean mass in both groups (control r⫽.83; DMD r⫽.66). SAM Calibration After the final calibration of the SAM, the number of steps it recorded during the slow and fast walk did not differ from the number of steps that were manually counted for any of the subjects. Step Rate During Community Activities The day of the week (weekend vs weekday) had no significant effect on the step data; therefore, the average of the 3 days for each subject was used for comparisons between the 2 groups. There was no difference in the average number of steps taken each day at the LSR (control, 1369⫾85; DMD, 1260⫾103). However, the average number of steps per day at the MSR (control, 2090⫾169;
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Fig 2. (Continued)
DMD, 1500⫾195; P⫽.028) and HSR (control, 2852⫾366; DMD, 1696⫾287; P⫽.022) were significantly higher in the control group than in the DMD group, and the total number of steps per Table 1: Anthropometric and Strength Characteristics Characteristics
Control Group
DMD Group
Age (y) Body mass (kg) BMI (kg/m2) Total fat (kg) Total lean (kg) Body fat (%) Total lean (%) Thigh lean (kg) Thigh lean/body mass (kg/kg) Knee extension strength (Nm) Knee extension strength/body mass (Nm/kg) Knee extension strength/thigh lean mass (Nm/kg)
9.5⫾2.1 32.7⫾9.7 17.0⫾2.3 7.4⫾3.8 24.1⫾7.0 21.9⫾5.7 74.9⫾5.6 2.5⫾0.9 0.08⫾0.01 61.6⫾29.4
9.1⫾2.1 29.4⫾12.1 18.0⫾5.5 9.1⫾8.4 18.9⫾4.0* 27.6⫾11.0 69.9⫾10.6 1.6⫾0.5* 0.06⫾0.01* 9.96⫾7.0*
1.82⫾0.47
0.35⫾0.25*
24.6⫾6.6
6.0⫾3.8*
NOTE. Values are mean ⫾ standard deviation. *DMD significantly different from control (P⬍.05).
day (control, 6311⫾493; DMD, 4456⫾513; P⫽.014) was also higher in the control group (fig 3). There was no difference in the number of hours the 2 groups wore the step monitor each day (control, 779⫾178min; DMD, 856⫾170min) as determined by the data in the diaries. However, the DMD boys spent significantly more total minutes inactive each day (control, 1028⫾19min; DMD, 1095⫾23min; P⫽.028) (fig 4). There was no difference in the time spent at the LSR (control, 245⫾10min; DMD, 235⫾19min), but the control boys spent significantly more time at the MSR (control, 94⫾7min; DMD, 66⫾8min; P⫽.010) and HSR (control, 72⫾9min; DMD, 43⫾7min; P⫽.018). Data were lost with the HRMs for several reasons. The chest strap was either worn incorrectly or not worn at all because of the discomfort it caused. Some subjects ignored instructions not to alter the watch settings, and data were lost due to recording errors. Equal numbers of control boys and boys with DMD were lacking heart rate data and there was no common pattern among the boys with the missing data. Heart Rate During Community Activities Figure 5 shows the mean heart rate recorded from both groups at the defined step rates (inactive, LSR, MSR, HSR). Arch Phys Med Rehabil Vol 86, April 2005
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Fig 3. Average steps per day at each of the step rates during 3 days of community ambulation for control and DMD groups. *Control and DMD groups differed significantly from each other (P<.05). Values are mean ⴞ standard error (SE).
The dependent variable (mean heart rate) was compared at the 4 step rates for each subject in both the control and DMD groups. Repeated-measures ANOVA analysis found no disease effect (P⫽.111) but did find a significant increase in heart rate with an increase in step rate (P⫽.000) and a significant interaction between step rate and disease (P⫽.000). Student t test analysis found that the heart rate of the DMD boys was significantly higher than that of the control boys at rest (P⫽.001) and at the LSR (P⫽.004); at the MSR and the HSR, there was no difference between the 2 groups. The maximum heart rate recorded during the 3 days of community activity was significantly lower in the DMD subjects (164⫾8 beats/min) than in the control subjects (209⫾4 beats/min) (P⫽.000). Over the 3-day period, the average correlation between step rate and heart rate was .477 for control boys but only .295 for the boys with DMD.
Fig 4. Average minutes per day spent at each of the step rates during 3 days of community ambulation for control and DMD groups. *Control and DMD groups differed significantly from each other (P<.05). Values are mean ⴞ SE.
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Fig 5. Mean heart rate for the control and DMD groups at each of the step rates recorded during the 3 days of community ambulation. * Control group differed significantly from DMD group (P<.05). Values are mean ⴞ SE.
Clinical Measurements Correlated With Age and Step Activity To examine whether a relation existed between total steps per day and the physical characteristics examined (strength, body composition), correlation coefficients were calculated (table 2). Total steps per day during the 3-day community activity correlated negatively with BMI (r⫽–.52) and percentage of body fat (r⫽–.67) in the group with DMD but not in the control group. As shown in figure 6, knee extension strength normalized for body mass increased with age in the control group (r⫽.68), but it decreased with age in the DMD group (r⫽–.57). In the control group, knee extension strength and knee extension strength normalized for thigh lean mass significantly increased with age (r⫽.86 and r⫽.49, respectively) but did not show an increase with age in the DMD group. The latter group showed a significant decrease in thigh lean mass with age, whereas the control group did not change significantly with age. DISCUSSION This is the first study to show the usefulness of the SAM for the quantitative evaluation of the physical activity of disabled children in the real-world community environment. The programmability of the SAM allows adjustments that accommodate variations in gait and makes possible an accurate record of each step taken. The results show the ability of the SAM to effectively quantify differences in intensity of activity by measuring the minute-by-minute step rate and to determine differences in the total time spent at specifically defined step rates. The output from the SAM also provides data that allow graphical presentation of the patterns of activity, as shown in figures 2A and 2C. Evaluation of these data allows for characterization of the activities throughout the day or during the recording period. Our results show that young boys with DMD, who are still functional and mobile, have significantly lower levels of higherintensity physical activities (eg, continuous walking, running) and significantly more inactive time each day. Although these children may be able to ambulate short distances in a clinic setting, their ambulatory function in the community may be more impaired than a clinician realizes. Among DMD subjects, there were strong
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STEP ACTIVITY IN DUCHENNE DYSTROPHY, McDonald Table 2: Correlations With Age and Total Steps per Day Age
Total Steps/Day
Characteristic
Controls
DMD
Controls
DMD
Age BMI Body fat (%) Thigh lean/body mass Knee extension strength Knee extension strength/thigh lean Knee extension strength/body mass
— .36 .14 –.23 .86* .49* .68*
— .01 .46 –.60* –.09 –.42 –.57*
–.39 –.16 –.09 –.31 –.20 .11 –.11
–.44 –.52* –.67* .39 –.18 .19 .27
*Significant correlation (Bonferroni, P ⬍ .05).
correlations between the functionally relevant step activity and the clinical measures that are affected by the dystrophic myopathy, including strength and secondary changes in body composition and BMI. These measures appear to be important correlates of ambulatory activity in children with DMD and are easily obtained in a clinical setting. Step activity determinations can monitor changes in functional level, disease progression, and response to therapeutic interventions. Lower-extremity strength values obtained with manual muscle testing and walking speed have been shown to correlate with loss of ambulatory function in DMD.3 The everyday activity of the boys with DMD could be affected by complex factors. Conversely, there was no correlation for the control subjects between any of the strength or body composition measurements and the total average daily steps. In disabled children there may be a critical value where strength loss and change in body composition (lean tissue loss and/or increase in body fat) is associated with a decline in step activity. None of the control subjects had this degree of strength or lean tissue loss, suggesting that their daily activity is more strongly influenced by factors other than strength and body composition parameters— for example, psychosocial or environmental factors, social roles and tasks, or aerobic fitness. In previous studies, HRM was used as a continuous quantitative measure of physical activity in children.4-6 However, HRM can be misleading as a measure of physical activity because heart rate may be influenced by factors other than activity, such as emotion, environmental temperature, body position, fitness level, and type
Fig 6. Change in knee extensor strength per kilogram of body mass with age for the control and DMD groups.
of activity.7 It is particularly difficult to evaluate low level activities through heart rate, because it has little or no change below a threshold heart rate (the flex point).8 This was evident in the boys with DMD who had a relatively poor correlation between heart rate and step activity (r⫽.29), presumably because of their low activity levels. However, the controls had a relatively good correlation between step activity and heart rate (r⫽.48). The lack of correlation between step rate and heart rate in boys with DMD could result from the heart’s inability to respond to increases in activity. As shown in figure 5, the heart rate of the boys with DMD was significantly higher than that of the control subjects at rest and low activity but did not differ at the higher step rates. This higher resting heart rate is not likely to be caused by simple deconditioning, because deconditioned able-bodied people show a large heart rate increase with increased physical activity; in contrast, the DMD boys had a much reduced response to increases in activity. The inability of the heart to respond to such increases may be related to the inappropriate sinus tachycardia observed in DMD.9-11 Sockolov et al11 reported that DMD subjects were unable to substantially increase their cardiac output during submaximal work. The possibility that DMD subjects may exhibit chronotropic incompetence is important in that it has been predictive of all-cause mortality in adults, even after accounting for age, physical fitness, and standard cardiovascular risk factors.12-16 CONCLUSIONS Our study shows that the SAM can be calibrated to accurately record the steps of subjects with DMD, who may have abnormal gait. Because of its ability to record the intensity, duration, and frequency of steps taken during community ambulation, it may be a useful device with which to evaluate therapeutic interventions geared at improving the functional status of children with DMD and other disabilities. We found that the DMD boys were more inactive and spent less time at MSRs and HSRs than did our control group. As a consequence, they took fewer total steps each day and significantly fewer steps at the MSR and HSR. The DMD children also had higher heart rates while inactive and at LSRs. Their heart rate response to increasing step rates was blunted when compared with the heart rate response of the control children. The total steps taken each day correlated with the BMI, percentage of body fat, and knee extensor strength in the DMD group, but they did not correlate in the control group. Step activity monitoring using the SAM appears to be a useful, objective, and unobtrusive method of quantitatively and continuously measuring the overall physical activity level and pattern of ambulatory activity of children with disabilities who have reduced ambulatory function and who may have abnormal gait patterns. Arch Phys Med Rehabil Vol 86, April 2005
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Acknowledgment: We acknowledge the valuable contributions of Kim Coleman, MS, for her technical assistance with the SAM. References 1. Coleman KL, Smith DG, Boone DA, Joseph AW, del Aguila MA. Step Activity Monitor: long-term, continuous recording of ambulatory function. J Rehabil Res Dev 1999;36:8-18. 2. McDonald CM, Widman L, Abresch RT, Walsh SA, Walsh DD. Utility of a step activity monitor for the measurement of daily ambulatory activity in children. Arch Phys Med Rehabil 2005;86: 793-801. 3. McDonald CM, Walsh DD, Widman L, Walsh SA, Coleman K. Use of the Step Activity Monitor for continuous objective threeday physical activity monitoring [abstract]. Dev Med Child Neurol 1999;80(Suppl):36. 4. Meijer GA, Westerterp KR, Koper H, Ten Hoor F. Assessment of energy expenditure by recording heart rate and body acceleration. Med Sci Sports Exerc 1989;21:343-7. 5. Livingstone MB, Robson PJ, Totton M. Energy expenditure by heart rate in children: an evaluation of calibration techniques. Med Sci Sports Exerc 2000;32:1513-9. 6. Maffeis C, Zaffanello M, Pinelli L, Schutz Y. Total energy expenditure and patterns of activity in 8 –10-year-old obese and nonobese children. J Pediatr Gastroenterol Nutr 1996;23:256-61. 7. McArdle WD, Katch FI, Katch VL. Exercise physiology. Baltimore: Williams & Wilkins; 1996. 8. Leonard WR. Measuring human energy expenditure: what have we learned from the flex-heart rate method? Am J Human Biol 2003;15:479-89. 9. D’Orsogna L, O’Shea JP, Miller G. Cardiomyopathy of Duchenne muscular dystrophy. Pediatr Cardiol 1988;9:205-13.
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10. Finsterer J, Stollberger C. The heart in human dystrophinopathies. Cardiology 2003;99:1-19. 11. Sockolov R, Irwin B, Dressendorfer RH, Bernauer EM. Exercise performance in 6-to-11-year-old boys with Duchenne muscular dystrophy. Arch Phys Med Rehabil 1977;58:195-201. 12. Lauer MS, Okin PM, Larson MG, Evans JC, Levy D. Impaired heart rate response to graded exercise. Prognostic implications of chronotropic incompetence in the Framingham Heart Study. Circulation 1996;93:1520-6. 13. Lauer MS, Francis GS, Okin PM, Pashkow FJ, Snader CE, Marwick TH. Impaired chronotropic response to exercise stress testing as a predictor of mortality. JAMA 1999;281:524-9. 14. Lauer MS, Mehta R, Pashkow FJ, Okin PM, Lee K, Marwick TH. Association of chronotropic incompetence with echocardiographic ischemia and prognosis. J Am Coll Cardiol 1998; 32:1280-6. 15. Dresing TJ, Blackstone EH, Pashkow FJ, Snader CE, Marwick TH, Lauer MS. Usefulness of impaired chronotropic response to exercise as a predictor of mortality, independent of the severity of coronary artery disease. Am J Cardiol 2000;86:602-9. 16. Pollock SG, Abbott RD, Boucher CA, Beller GA, Kaul S. Independent and incremental prognostic value of tests performed in hierarchical order to evaluate patients with suspected coronary artery disease. Validation of models based on these tests. Circulation 1992;85:237-48. a. b. c. d.
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