A New Method of Using Heart Rate to Represent Energy Expenditure: The Total Heart Beat Index

1266 A New Method of Using Heart Rate to Represent Energy Expenditure: The Total Heart Beat Index Victoria L. Hood, MSc, Malcolm H. Granat, PhD, Douglas J. Maxwell, BSc, John P. Hasler, MPhil ABSTRACT. Hood VL, Granat MH, Maxwell DJ, Hasler JP. A new method of using heart rate to represent energy expenditure: the Total Heart Beat Index. Arch Phys Med Rehabil 2002;83:1266-73. Objectives: To develop a new method of representing energy expenditure using heart rate and to determine its reproducibility compared with the criterion standard of oxygen cost. Design: Repeated-measures design. Setting: University gait analysis laboratory and gymnasium at 2 spinal injury units. Participants: Twenty unimpaired adults and 17 subjects with spinal cord injury (SCI). Interventions: Not applicable. Main Outcome Measures: Heart rate and oxygen consumption were measured on 20 unimpaired adults walking under controlled steady-state and nonsteady-state conditions. New methods of estimating energy expenditure by using heart rate were compared with oxygen consumption, oxygen cost, and Physiological Cost Index (PCI). Nine subjects with SCI, walking with and without functional electric stimulation, were assessed to determine use of these new measures with this group. Sensitivity to change of the new measurement techniques was investigated in 10 subjects with SCI, comparing wheelchair pushing to walking. Results: The Total Heart Beat Index (THBI) was developed as a new index, calculated by dividing the total heartbeats during activity by distance traveled. High repeatability was found under steady-state and nonsteady-state conditions (intraclass correlation coefficients,.893.995). Sensitivity to change in activity level was also shown. Conclusions: The THBI is a simple parameter to calculate from continuous heart rate data and provides a reproducible alternative to gas analysis and the PCI. Key Words: Energy expenditure; Gait; Heart rate; Rehabilitation; Spinal cord injuries. 2002 by the American Congress of Rehabilitation Medicine and the American Academy of Physical Medicine and Rehabilitation MOTOR IMPAIRMENTS FREQUENTLY result in increased energy expenditure, which may limit functional ability. 1 The energy requirement of standing and walking for individuals with spinal cord injury (SCI) is a factor that influences the use of walking orthoses. 2 For these reasons, energy From the Bioengineering Unit, University of Strathclyde (Hood, Granat, Maxwell) and Queen Elizabeth National Spinal Injuries Unit, Southern General Hospital (Hasler), Glasgow, Scotland. Supported by the Engineering and Physical Sciences Research Council. No commercial party having a direct financial interest in the results of the research supporting this article has or will confer a benefit upon the author(s) or upon any organization with which the author(s) is/are associated. Reprint requests to Malcolm H. Granat, PhD, Bioengineering Unit, University of Strathclyde, 106 Rottenrow, Glasgow G4 ONW, Scotland, e-mail: m.h.granat@strath.ac.uk. 0003-9993/02/8309-6944$35.00/0 doi:10.1053/apmr.2002.34598 expenditure is an important consideration in the design and prescription of self-powered mobility aids. Energy expenditure has traditionally been measured either by indirect calorimetry or by the Physiological Cost Index (PCI). Indirect calorimetry is based on the assumption that all energy-releasing reactions in the body ultimately depend on oxygen uptake, 3 and is the most widely accepted standard. 1,4,5 The most common method of measuring oxygen uptake during exercise is by open-loop spirometry when exhaled air is sampled and analyzed for its oxygen content. Recent developments have led to lightweight, portable telemetric devices that are capable of performing breath-by-breath oxygen and carbon dioxide analysis. Oxygen uptake is expressed either in unit time (V O2,inmL kg 1 min 1 ) or in unit distance (oxygen cost, in ml kg 1 m 1 ), which can be considered as a measure of metabolic efficiency. 5 The PCI, developed by MacGregor, 6 is calculated by dividing the difference between the steady-state walking and resting heart rates by the walking velocity. This index provides a measure of gait efficiency in heartbeats per meter. The PCI was proposed as an alternative to V O2 measurements because a linear relationship exists between heart rate and oxygen uptake for an individual at submaximal workloads. 7 The PCI can be easily calculated and has been used extensively in clinical and research settings. 8-11 Several researchers 1,4,5,12 have performed repeatability studies on both V O2 and the PCI by using subjects with and without motor impairments. They have found that oxygen uptake is more repeatable and less variable than the PCI, supporting the use of gas analysis for clinical gait analysis. V O2 measurements, however, require equipment that is cumbersome and may cause discomfort to the user, possibly affecting the results obtained and reducing its suitability for some subject groups, especially young children. 9,13 Some researchers 6,9,13 have reported good repeatability with the PCI in investigations of unimpaired subjects. A considerable emphasis in their methodology is that the working heart rate must achieve a steady state. In unimpaired subjects, this state occurs when the cardiovascular system has adapted to the new physiologic demands, which occurs about the third minute of exercise. 7 In a population with gait impairments, the effort of walking may be significantly higher and not be considered submaximal. Boyd et al 1 investigated children with cerebral palsy and discovered that, in 9% of their subjects, heart rate continued to rise during the walking trials, whereas gas analysis showed the onset of anaerobic activity. Similar findings have been reported in SCI gait with some subjects fatiguing before steady-state conditions were attained. 11 In these subjects, it is impossible to calculate the PCI by the method originally presented by MacGregor, 6 and if a nonsteady-state heart rate is used as an alternative, then the repeatability may be compromised. 13 Some investigators using the PCI may have inadvertently used nonsteady-state conditions by sampling heart rate only at the end of a walk of short duration. Burridge et al 14 used the PCI as an outcome measure to assess the benefits of the Odstock Dropped Foot Stimulator. The PCI was determined by

TOTAL HEART BEAT INDEX, Hood 1267 initial period of rehabilitation and were skilled users of their walking systems. Informed consent was obtained from all subjects before testing, and the study was approved by local ethics committees. Physiologic Assessment Equipment Portable breath-by-breath gas analysis was performed by using the Cosmed K4 b 2 analyzer. a The Polar Accurex Plus b was used to sample heart rate at 5-second intervals. Fig 1. A schematic of heart rate plotted against time during exercise: Area 1 represents the extra heartbeats required during exercise; areas 1 2, the total number of heartbeats during the exercise including the basal level. Area 3 represents the extra heartbeats that occur during the recovery phase; areas 3 4, the total heartbeats occurring during recovery. using the heart rate attained at the end of a 10-m walk, rather than the traditional steady-state working heart rate. On average, the 10-m walk took subjects 16 seconds, an insufficient time for steady-state conditions to be attained. Continuous heart rate monitoring is now readily available with development of portable heart rate monitors. To represent more accurately the total energy consumed during an activity, we proposed to investigate heart rate behavior throughout a period of exercise by finding the total number of heartbeats that occurred during the period. This is represented in figure 1 by the area under the heart rate versus the time curve. Four areas of this figure were considered: the extra number of heartbeats required during exercise (area 1), the total number of heartbeats during exercise (areas 1 2), the extra number of heartbeats during recovery (area 3), and the total number of heartbeats during recovery (areas 3 4). It was hypothesized that calculating an index based on the number of heartbeats would provide a measure of a person s total energy consumption and that this measure would be independent of whether the activity was steady or nonsteady state. By including the recovery period, the repayment of the oxygen debt that occurs at the onset of exercise is included. The purpose of the present study was to determine if the number of heartbeats during activity and/or recovery could be used to produce an index of gait efficiency that would be repeatable and reliable compared with oxygen uptake and sensitive enough to measure intervention effects in a population with gait impairments. METHOD Participants Twenty subjects (14 men, 6 women) with no motor impairments were included in the study (table 1). Subjects were excluded from testing if they had any cardiovascular, neuromuscular, or respiratory disorders or if they had recently recovered from a viral infection. A high level of physical fitness was not essential, but subjects were required to maintain a brisk walking pace for 5 minutes. Seventeen subjects (15 men, 2 women) with SCI were recruited from 2 spinal injury units, the Queen Elizabeth National Spinal Injuries Unit, Glasgow, and the Regional Spinal Injuries Unit, Southport, England (table 2). All had completed their Procedure Testing was initially performed on the unimpaired subjects. They attended the gait analysis laboratory on 2 occasions, at the same time of day, and within a 7-day period. They were asked not to eat, drink, or smoke within the 2 hours preceding the test. On arrival, subjects were weighed, measured, and fitted with the Polar monitor and Cosmed K4. Two tests were performed on the unimpaired subjects, and data were collected throughout the period of the tests. The steady-state test consisted of a 5-minute period of quiet rest, 10 minutes of walking at self-selected walking speed around a 25-m figure of 8 track, and a final 5-minute rest period. Once heart rate had recovered to baseline, the nonsteady-state test was performed. This consisted of a 3-minute period of quiet rest, 2 minutes of standing, 5 minutes of walking on a treadmill with workload being increased at 1-minute intervals to prevent heart rate achieving steady-state, and then a final 5-minute rest period. The increase in workload on the treadmill followed the Bruce protocol as shown in table 3, which was modified to 1 minute of walking at each intensity level to prevent steady-state conditions. 7 Tests were performed under the same conditions and order on the second day. The SCI subjects were divided into 2 groups: group A (n 11) and group B (n 9). Group A subjects were tested under 2 conditions, using their preferred method of mobility (generally wheelchair) followed by walking with their orthoses. For each condition, a standard test of 5-minute rest, 10- minute activity (either walk or wheelchair push), and then 5-minute rest was performed as with the unimpaired subjects. If group A subjects were unable to complete the 10-minute walk because of fatigue, their time and distance walked were recorded. Data were collected by using the Cosmed K4 and Polar Accurex Plus. Group B consisted of 9 subjects who were participating in a European study investigating functional electric stimulation (FES) assisted walking (the CREST project). 15 They attended on 2 consecutive days, and on each occasion walked first using FES and then with their normal mobility aid. They walked continuously around a figure of 8 track for a period of 6 minutes while heart rate was collected by using the Polar monitor. Oxygen consumption data were not collected from subjects in group B. Outcome Measures Lap times and total walking distances were recorded to calculate speed in meters per minute. Raw data from the Table 1: Unimpaired Subject Profiles (n 20) Mean SD Range Age (y) 26.6 6.3 16 45 Weight (kg) 74.3 12.3 51 100 Height (m) 1.76 0.01 1.54 1.91 Abbreviation: SD, standard deviation.

1268 TOTAL HEART BEAT INDEX, Hood Table 2: Profiles of Subjects With SCI (n 17) Subject Age (y) Weight (kg) Height (m) Injury Level Normal Mobility Method Alternative Mobility Method 1 19 69.0 1.60 T7 (I) Wheelchair FES and AFO 2 25 61.4 1.80 C5 6 (I) Swing through gait FES 4-point gait 3 35 90.0 1.78 T6 (I) Wheelchair KAFO on left leg 4 51 69.7 1.65 C7 (I) Walk with rollator Wheelchair 5 42 120.0 1.93 T12 (I) Wheelchair FES and walker 6 28 60.5 1.75 T7 (I) Walk with crutches FES 7 26 62.0 1.75 C6 (I) Wheelchair FES 8 30 94.0 1.75 T10 (I) AFO and stick FES 9 63 98.6 1.90 T6 (I) Walk with 2 sticks FES 10 42 88.0 1.88 C4 (I) Walk with crutches FES 11 31 99.8 1.80 C6 7 (I) Wheelchair RGO 12 48 73.0 1.81 T8 11 (C) Wheelchair RGO 13 40 73.3 1.85 T4 (C) Wheelchair RGO 14 31 63.9 1.50 T12 (C) Wheelchair RGO 15 46 74.2 1.80 T4 (C) Wheelchair RGO 16 31 67.1 1.85 T5 6 (C) Wheelchair RGO 17 57 67.4 1.81 T12 (I) Wheelchair RGO Abbreviations: I, incomplete; C, complete; AFO, ankle-foot orthosis; KAFO, knee-ankle-foot orthosis; RGO, reciprocal gait orthosis. Cosmed K4 and Polar Accurex Plus were plotted against time to determine if a steady state had been attained. The following parameters were calculated: (1) the PCI by using MacGregor s formula: PCI (HR (SS) HR (R) )/velocity, where HR (SS) was the average steady-state working heart rate and HR (R) was the average resting heart rate; (2) oxygen consumption during steady-state exercise (calculated from raw data to derive V O2,inmL kg 1 min 1 ); (3) oxygen cost (calculated by dividing oxygen consumption by velocity); (4) the total number of heartbeats during exercise (calculated by the number of beats that occurred in each 5-s sample period and then summing these values for the whole of the exercise period); (5) the total number of heartbeats during recovery (calculated by the number of beats that occurred in each 5-s sample period and then summing these values for the period of time from finishing exercise until the heart rate had returned to within a beat of resting levels); (6) the extra heartbeats during exercise (calculated by the number of beats that occurred as a result of the resting heart rate over the time period of exercise and then subtracting that from the total number of beats during exercise); (7) the extra heartbeats during recovery (calculated by the number of beats that occurred due to resting heart rate in the recovery period and then subtracting that from the total beats that occurred in the recovery period); and (8) the Total Heart Beat Index (THBI; calculated by dividing the total number of beats during exercise by the total distance traveled in that time period). For the nonsteady-state test with unimpaired subjects, it was impossible to calculate the PCI, oxygen consumption, and oxygen cost by traditional methods because the steady-state Table 3: Modified Bruce Treadmill Protocol Stage I II III IV V Minutes 1 1 1 1 1 Speed (ms 1 ) 0.76 1.11 1.51 1.87 2.22 Gradient (%) 10 12 14 16 18 Distance (m) 45.3 66.7 90.7 112 133.3 NOTE. Subjects walked for 1 minute at each exercise intensity and then continued to the next stage without stopping. Total distance covered was 447m. condition was not attained. An average value of heart rate and oxygen consumption was used from the 5-minute period of walking to calculate the PCI and oxygen cost in these trials divided by the average velocity. Statistical Analysis Reproducibility in the present study was assessed by intraclass correlation coefficient 16,17 (ICC) and by calculating the smallest detectable difference 5 (SDD). One-way analysis of variance was conducted to determine the between-subject (BMS) and within-subject (WMS) mean squares. ICC 1,1 was calculated as described by Rankin and Stokes 17 : ICC 1,1 BMS WMS BMS WMS An ICC of 1.0 represents complete repeatability of a measure (ie, that there is no within-subject variation for the 2 tests). The greater the variation of the measurement on the 2 occasions, the larger WMS will be, and therefore a lower ICC will result. ICCs can be used to compare groups with different sample size; however, an ICC will appear high if there is a large variance in a group. For this reason we used an ICC in conjunction with SDD. The SDD is the point when the difference between 2 assessments exceeds the standard error of measurement (SE m )of those assessments (ie, the point at which a change can be considered a real difference and not purely error). The 95% confidence interval (CI) of the SDD was achieved by selecting the appropriate 2-tailed t value for the sample size that allows comparison of groups with different numbers of subjects 5 : SE m WMS SDD (appropriate t value for 95% CI) 2 SE m The SDD was also expressed as a percentage of the group mean for the set of measurements investigated (SDD%) to normalize and allow comparisons between variables with different ranges. For a measurement tool to be useful, it is ideal for it to have a low SDD so that small changes in measured values can be detected. Sensitivity to change in workload was determined for the SCI subjects who were tested under 2 conditions by calculating

TOTAL HEART BEAT INDEX, Hood 1269 Fig 2. Typical heart rate and oxygen uptake profile for an unimpaired subject performing a 10-minute walking test. the percentage increase in the parameter from wheelchair push to walking. RESULTS Heart Rate and V O2 Profiles for Unimpaired Subjects Because of technical problems with the oxygen sensor of the Cosmed K4, which had to be replaced midtrial, only 10 normal subjects underwent repeat gas analysis. Heart rate monitoring was repeated in all 20 unimpaired subjects. During the 10-minute continuous walking test, all subjects had similar heart rate and V O2 profiles (fig 2). On commencing walking, there was a rapid increase in both V O2 and heart rate. In all cases, steady state was attained by the third minute of walking. All outcome measures for these assessments are given in table 4. In the nonsteady-state treadmill test, V O2 and heart rate continued to rise throughout in all subjects, making it a good model for nonsteady-state conditions (fig 3). Because a steady state of V O2 and heart rate was not attained, it was not possible to calculate the PCI or to give a value for V O2 or oxygen cost Fig 3. Typical heart rate and oxygen uptake profile for a unimpaired subject during the treadmill test. that would represent the whole trial. All other heart rate parameters were calculated (table 4). Under both steady-state and nonsteady-state conditions, oxygen consumption and heart rate were related in a linear fashion for each subject. Plotting heart rate against oxygen consumption throughout the test produced a straight line, an expected result for submaximal loads. 7 The gradient of this line differed between individuals, reflecting the different levels of cardiovascular fitness. Repeatability in Unimpaired Subjects Table 4 summarizes the ICCs and SDDs for steady-state and nonsteady-state testing for unimpaired subjects. ICCs were high for V O2 (.892) but lower for oxygen cost and the PCI (.686,.744, respectively) under steady-state conditions. Under nonsteady state, using the averaged heart rate or oxygen uptake, ICCs were high for V O2 and oxygen cost (.850) but lower for the PCI (.589). For the new outcomes measures using heartbeats, ICCs were highest for the outcome that used the total beats that occurred during exercise (.897 for steady state; Table 4: Reproducibility Statistics for Unimpaired Subjects Measurement n* Mean SD ICC 1,1 SDD SDD% Steady state V O2 (ml kg 1 min 1 ) 10 12.1 2.0.892 2.01 16.6 Oxygen cost (ml kg 1 m 1 ) 10 0.17 0.02.686 0.03 16.5 PCI (beats/m) 20 0.33 0.09.744 0.14 42.4 Total beats during exercise 20 938 139.897 133 14.2 Total beats during recovery 17 73 59.296 149 204.3 Extra beats during exercise 20 228 58.647 101 44.6 Extra beats during recovery 17 8.5 5.4.441 12.1 142.7 THBI (beats/m) 20 1.40 0.33.950 0.22 15.7 Nonsteady state V O2 (ml kg 1 min 1 ) 10 16.8 2.8.850 2.88 17.2 Oxygen cost (ml kg 1 m 1 ) 10 0.19 0.03.850 0.03 17.2 PCI (beats/m) 18 0.44 0.08.589 0.16 37.6 Total beats during exercise 18 555 79.893 81 14.5 Total beats during recovery 15 131 68.517 143 109.7 Extra beats during exercise 18 196 38.589 74 37.6 Extra beats during recovery 15 39 14.599 27 68.7 THBI (beats/m) 18 1.24 0.18.893 0.18 14.5 * Number of subjects with repeat data is variable because of equipment failure or the failure to recover heart rate to baseline within a 5-minute period. Calculated by using average heart rate or oxygen consumption, and the average velocity.

1270 TOTAL HEART BEAT INDEX, Hood Fig 4. Measurements from steady-state trials of unimpaired subjects on 2 separate days plotted against each other. Oxygen consumption and the THBI show greatest linearity and therefore highest repeatability..893 for nonsteady state). The outcome measures that incorporated the recovery period were found to have lowest reproducibility (ICCs,.296.599). Because 3 subjects for the steady state and 5 for the nonsteady state failed to recover, we decided not to include recovery heart rate in the new index. The outcome measure of total heartbeats during exercise, for both steady-state and nonsteady-state conditions (ICC,.897.893), was more reproducible than the outcome measure of extra beats during exercise (ICC,.647.589). The SDD% was low for V O2 and oxygen cost (16.6%, 16.5%, respectively) and was larger for the PCI (42.4%) under steady-state conditions. Under nonsteady-state conditions, the SDD% for V O2 and oxygen cost was low (17.2%) but was larger for the PCI (37.6%). For the new outcome measure using heartbeats, the total beats during exercise had the lowest SDD% (14.2% for steady state, 14.5% for nonsteady state). Outcome measures that included the recovery period or subtracted resting heart rates had much higher SDDs. The total heartbeats during the exercise had the best repeatability of the new outcome measures. This measure was converted into an index of energy efficiency by dividing it by the distance walked in that time period. This was termed the THBI and had a high ICC under steady- and nonsteady-state exercise (.950,.893, respectively) and a low SDD% (15.7%, 14.5%, respectively). Measurements from the repeated tests plotted against each other (fig 4) show the repeatability. The charts for oxygen consumption and the THBI are linear, indicating high repeatability for these measurements in unimpaired subjects. Oxygen Cost and Heart Rate Relationships To assess the relationship between the THBI and oxygen cost, the Pearson product-moment correlation was calculated. For the group of subjects under steady-state conditions, a poor nonsignificant relationship (r.150) was found. The correlation between the PCI and oxygen cost was also poor and not significant (r.139). Heart Rate and V O2 Profiles for SCI Subjects In the 11 subjects with SCI who underwent gas analysis and heart rate monitoring, there was no typical response for the behavior of heart rate and V O2 during the activity. In 8 subjects, heart rate continued to increase over the duration of the walk, with no steady state being attained. In these subjects the PCI was not calculated because a steady-state working heart rate could not be determined. Oxygen uptake did not achieve steady state in 3 walking trials, and therefore we could not obtain a value for oxygen consumption for these subjects. Figure 5 shows the nonsteady-state heart rate behavior of a subject walking with FES. In the CREST project, 8 subjects had repeat data for FESassisted walking, and all 9 subjects had repeat data for independent walking. In 16 of these 34 trials, subjects did not achieve a steady-state heart rate over the 6-minute walking period, and therefore the PCI was not calculated (table 5). Repeatability in SCI Subjects ICCs and the SDD for the PCI and THBI were calculated for the 9 subjects who were part of the CREST project (table 6).

TOTAL HEART BEAT INDEX, Hood 1271 Table 6: Repeatability Statistics for Subjects With SCI Walking With and Without FES Measurement n Mean SD ICC 1,1 SDD SDD% Walking with FES PCI (beats/m) 5 5.73 4.61.961 3.77 65.8 THBI (beats/m) 8 14.66 13.5.965 7.99 54.5 Walking without FES PCI (beats/m) 3 1.30 0.97.939 1.58 121.5 THBI (beats/m) 9 16.59 21.24.995 4.43 26.7 NOTE. Number of subjects (n) with repeated data is lower for the PCI because some trials did not achieve steady state. Fig 5. Heart rate and oxygen consumption for subject 3 walking with FES. Both parameters continue to rise throughout the walk. These subjects walked with and without their individualized FES systems. One subject had a change of FES system on the second trial and was excluded from this analysis. Because of the large number of nonsteady-state trials, only 5 subjects had repeat data for the PCI when walking with FES and only 3 when walking independently. ICCs were high (.939.995) for all conditions, but the SDD was very large for the PCI under both conditions (65.8%, 121.5%, respectively) and for the THBI for the subjects walking with FES (54.5%). Sensitivity to Change in Activity Level Four subjects had steady-state data for oxygen consumption, oxygen cost, and the THBI for both wheelchair pushing and walking. In another 3 subjects, oxygen consumption could be averaged over the last 3 minutes of the test because steady state was not achieved, providing a good estimate of oxygen cost. The PCI could not be included because steady-state data were missing in the majority of trials. The percentage change in each variable between the wheelchair test (low effort) and the walking test (high effort) is shown in figure 6. Paired t tests performed on the data found no significant change in oxygen consumption at the 2 levels of effort (t.63, P.55). Oxygen cost and the THBI both showed significant difference between the 2 conditions (t 13.45, P.05; t 9.74, P.05). The sensitivity of the THBI was similar to the criterion standard of oxygen cost. DISCUSSION With the current emphasis on evidence-based practice, it is important to quantify the effect of interventions. A measurement tool should be accurate, reliable, sensitive to change, and yet also minimally encumbering to the subject. In the present study, unimpaired subjects and subjects with an SCI were assessed by using gas analysis and heart rate monitoring. In unimpaired subjects, calculating the commonly used energy consumption parameters of V O2, oxygen cost, and the PCI presented no problems because subjects attained steady state within 3 minutes of the 10-minute walking trial. For subjects with SCI, 73% did not achieve a steady-state heart rate over a 10-minute walk, and for these subjects the PCI could not be calculated. Problems with subjects not achieving steady-state heart rate have been noted previously in the literature, 1,11 but little has been reported on oxygen consumption failing to achieve steady state. Boyd et al 1 found that 9% of children with cerebral palsy did not attain a steady state of oxygen cost during a 10-minute walk. In the present study, 3 of our 11 SCI subjects (27%) did not attain a steady state of oxygen consumption over the 10-minute trial, making it difficult to give an exact measure of oxygen uptake or oxygen cost. To quantify the gait efficiency of persons who do not achieve steady state, a different method of analysis must be used. The present study proposed that, because of the known linear relationship between oxygen uptake and heart rate during submaximal exercise for any individual, 7 the total number of heartbeats during the exercise and recovery periods could represent the energy expenditure. This relationship was clearly observed when studying the profiles of heart rate and oxygen uptake for both SCI and unimpaired subjects during steady- and nonsteady-state trials (figs 2, 3, 5), with heart rate showing a close association to oxygen uptake in all trials. Because the relationship between heart rate and oxygen uptake is related to the individual s aerobic fitness, 3,7 there is a poor correlation between oxygen cost and the PCI or THBI (r 1.39, r.150, respectively) for the group data. This finding limits the use of heart rate indices to trials that assess the effect of a change in conditions on individuals. Any change in the heart rate index in these cases will represent a change in oxygen consumption and therefore energy expenditure. From the heart rate, it is not possible to know precisely energy consumption, unless the heart rate to oxygen uptake ratio is known for that individual. Table 5: Number of Subjects With SCI Not Achieving Steady- State Heart Rate Over a 6-Minute Walk Group No. of Trials No. of Nonsteady- State Trials % of Trials Having Nonsteady-State Conditions Subjects without repeat data 11 8 73 Subjects from CREST project 34 16 47 Fig 6. The percentage change of V O2, oxygen cost, and THBI for each SCI subject, comparing wheelchair pushing and walking. * Oxygen consumption averaged over last 3 minutes of test.

1272 TOTAL HEART BEAT INDEX, Hood However, in many studies, the focus is on determining the effect of an intervention on a group of individuals. The recovery period has been used by others investigating energy consumption, 13,18 but it was found in the present study to be the least reproducible outcome measure. Also 3 unimpaired subjects did not recover to baseline heart rate within 5 minutes after a 10-minute walk, and 5 failed to recover after a treadmill test. In MacGregor s original article on the PCI, 6 he recommended including the resting heart rate so that the index would represent the energy increase that resulted from the activity. In the present study, we found that the total number of heartbeats during exercise was more repeatable than the extra number of heartbeats above resting values. Because resting heart rate is influenced by external factors, 7 the reproducibility of an outcome measure that includes this factor will be compromised. The most repeatable of the outcome measures using heart rate in the present study was the total number of heartbeats during the exercise period, which had an ICC of.897 for steady-state and.893 for nonsteady-state exercise. We consequently propose a new measure of energy efficiency, the THBI, calculated by dividing by the total number of heartbeats during exercise by the total distance traveled: Total heartbeats during exercise period THBI Total distance traveled m The THBI had very high reproducibility, with an ICC of.950 for steady-state exercise and an SDD% of only 15.7%, an improvement on the criterion standards of oxygen consumption, oxygen cost, and the PCI. An advantage of the THBI is that it can be used for nonsteady-state conditions when other criterion standards cannot. Under nonsteady-state conditions, we found the THBI had high reproducibility (ICC.893, SDD% 14.5%), again an improvement on oxygen consumption, oxygen cost, and the PCI obtained from averaging the data over the whole of the trial. It was not possible to perform repeat gas analysis on the SCI subjects in the present study. Repeat data on the THBI and the PCI was obtained from SCI subjects in the CREST project under 2 different conditions; walking with and without FES. When walking without FES, the THBI was found to have better reproducibility statistics than the PCI (ICC.995, SDD 26.7% vs ICC.939, SDD 121.5%). This level of reproducibility for the PCI is comparable to work reported previously. 1,5 The THBI compares favorably with reproducibility reported by Ijzerman et al 5 for oxygen cost in 10 reciprocal gait orthosis users (ICC.94, SDD% 33.7%). The results for walking with FES found high ICCs for the PCI and THBI (.961,.965, respectively), but large SDDs (65.8%, 54.5%, respectively). The high ICC along with a high SDD may be because of the large variance in each group. In this case, the value of the BMS is affected more than the WMS, tending to result in a greater ICC. Alternatively, the large SDD may have been caused by an actual change in the walking between days. It is possible that the electrodes for the FES were positioned differently or stimulation was different between the 2 days, resulting in an actual change in energy cost, making this test unsuitable as a reproducibility study. The subjects who performed both a wheelchair push and a walk all expressed that the effort required for walking was much higher than that of wheelchair pushing; therefore, the use of the wheelchair predominated for mobility. We expected that the energy consumption of walking would be much higher, but this was found not to be true, with oxygen consumption measures remaining the same (fig 6). This finding may be because of subjects pacing their walking speed, which resulted in a certain level of exertion. In this case, the measures of energy efficiency are more useful, with oxygen cost and the THBI both showing a significant increase for walking compared with the wheelchair push (P.05). The THBI generally followed a similar profile to oxygen cost, which showed that its sensitivity was similar to the criterion standard. To determine more accurately the degree of sensitivity to change in workload, further experimentation is warranted with larger numbers of subjects working at predetermined levels of exertion. CONCLUSION The THBI is proposed as a new index, capable of representing the energy efficiency of gait under both steady and nonsteady-state conditions. It is easy to calculate and requires equipment that is readily available, comfortable to wear, and noninvasive. Repeatability statistics found the THBI to be comparable to oxygen cost and better than the PCI. The THBI was found to be sensitive to change in workload, with a profile similar to that of oxygen cost. Many subjects with SCI do not achieve steady-state conditions when walking, either for heart rate or oxygen uptake. This new method would allow investigators to quantify energy expenditure during gait that previously has not been possible. As with all parameters involving the use of heart rate, it is impossible to convert the THBI into a measure of energy expenditure without determining each individuals V O2 to heart rate relationship. However, the THBI can be considered as a reflection of energy expenditure and may be used in comparative studies so long as the same subjects are used. Repeatability studies would be beneficial on a larger group of subjects, but based on the present study the THBI appears to be a valid alternative to the current criterion standards. Acknowledgments: We thank Ian Stallard and Professor Jack Edwards at the Regional Spinal Injuries Unit, Southport, for their assistance in organizing trials with SCI subjects, and Danny Rafferty at Glasgow Caledonian University for the access to the Cosmed K4. References 1. Boyd R, Fatone S, Rodda J, et al. High- or low-technology measurements of energy expenditure in clinical gait analysis? Dev Med Child Neurol 1999;41:676-82. 2. Sykes L, Campbell IG, Powell ES, Ross ER, Edwards J. Energy expenditure of walking for adult patients with spinal cord lesions using the reciprocating gait orthoses and functional electrical stimulation. Spinal Cord 1996;34:659-65. 3. McArdle WD, Katch FI, Katch VL. Exercise physiology: energy, nutrition and human performance. 4th ed. Baltimore: Williams & Wilkins; 1996. 4. 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