Effects of placement and orientation of body-fixed accelerometers on the assessment of energy expenditure during walking

Does Accelerometry at the Centre of Mass Accurately Predict the Gait Energy Expenditure in Patients with Hemiparesis?

BACKGROUND

The aim of this study was to compare energy expenditure (EE) predicted by accelerometery (EEAcc) with indirect calorimetry (EEMETA) in individuals with hemiparesis.

METHODS

Twenty-four participants (12 with stroke and 12 healthy controls) performed a six-minute walk test (6MWT) during which EEMETA was measured using a portable indirect calorimetry system and EEACC was calculated using Bouten's equation (1993) with data from a three-axis accelerometer positioned between L3 and L4.

RESULTS

The median EEMETA was 9.85 [8.18;11.89] W·kg-1 in the stroke group and 5.0 [4.56;5.46] W·kg-1 in the control group. The median EEACC was 8.57 [7.86;11.24] W·kg-1 in the control group and 8.2 [7.05;9.56] W·kg-1 in the stroke group. The EEACC and EEMETA were not significantly correlated in either the control (p = 0.8) or the stroke groups (p = 0.06). The Bland-Altman method showed a mean difference of 1.77 ± 3.65 W·kg-1 between the EEACC and EEMETA in the stroke group and -2.08 ± 1.59 W·kg-1 in the controls.

CONCLUSIONS

The accuracy of the predicted EE, based on the accelerometer and the equations proposed by Bouten et al., was low in individuals with hemiparesis and impaired gait. This combination (sensor and Bouten's equation) is not yet suitable for use as a stand-alone measure in clinical practice for the evaluation of hemiparetic patients.

Associations Between Physical Fitness, Objectively Measured Physical Activity and Academic Performance

There is evidence that physical activity (PA) can improve the academic performance. We recruited healthy adolescent girls, aged 11–12 years, and measured their PA with the accelerometer ActiGraph GT3X for the consecutive 5 days. Physical fitness (PF) was measured with eight motoric tests and three anthropometry measures. Academic performance (AP) was assessed for the six academic narrated school subjects. The results revealed that the girls were more physically active during the week days and less active at weekend (557 vs. 516 counts/min). Physical education grade shows the highest overall correlations with the results of the PF test battery (r = 0.53–0.95, p < 0.01). Nevertheless, correlations surprisingly decrease for the combined daily PA (r = 0.45), especially the weekend PA (r = 0.28). Grade point average and PF correlated moderately (r = 0.43-0.64), while they were moderate to high for PA (r = 0.59–0.87). Many questions arose after the completion of the present study and several new topics opened up, such as the question of how parental education affects the duration of PA and AP of the children and the influence of the place of residence AP of the children.

Acceleration Gait Measures as Proxies for Motor Skill of Walking: A Narrative Review

In adults 65 years or older, falls or other neuromotor dysfunctions are often framed as walking-related declines in motor skill; the frequent occurrence of such decline in walking-related motor skill motivates the need for an improved understanding of the motor skill of walking. Simple gait measurements, such as speed, do not provide adequate information about the quality of the body motion's translation during walking. Gait measures from accelerometers can enrich measurements of walking and motor performance. This review article will categorize the aspects of the motor skill of walking and review how trunk-acceleration gait measures during walking can be mapped to motor skill aspects, satisfying a clinical need to understand how well accelerometer measures assess gait. We will clarify how to leverage more complicated acceleration measures to make accurate motor skill decline predictions, thus furthering fall research in older adults.

Wearable oxygen uptake and energy expenditure monitors

Obesity is a major health issue in both developed and developing countries. The balance between energy intake and exercise is important, and measurements of both energy intake and energy expenditure are required. Many studies have attempted to monitor energy intake via wearable technology, but no standard methods have yet been developed for this purpose. This is in marked contrast to the long history of measurement and estimation of energy expenditure. Indirect calorimetry is commonly used in the laboratory. Energy expenditure associated with daily activity is the most important measure, although a number of alternative measures have also been proposed. This mini-review discusses the current status of energy expenditure measurement.

Behavioural compass: animal behaviour recognition using magnetometers

BACKGROUND

Animal-borne data loggers today often house several sensors recording simultaneously at high frequency. This offers opportunities to gain fine-scale insights into behaviour from individual-sensor as well as integrated multi-sensor data. In the context of behaviour recognition, even though accelerometers have been used extensively, magnetometers have recently been shown to detect specific behaviours that accelerometers miss. The prevalent constraint of limited training data necessitates the importance of identifying behaviours with high robustness to data from new individuals, and may require fusing data from both these sensors. However, no study yet has developed an end-to-end approach to recognise common animal behaviours such as foraging, locomotion, and resting from magnetometer data in a common classification framework capable of accommodating and comparing data from both sensors.

METHODS

We address this by first leveraging magnetometers' similarity to accelerometers to develop biomechanical descriptors of movement: we use the static component given by sensor tilt with respect to Earth's local magnetic field to estimate posture, and the dynamic component given by change in sensor tilt with time to characterise movement intensity and periodicity. We use these descriptors within an existing hybrid scheme that combines biomechanics and machine learning to recognise behaviour. We showcase the utility of our method on triaxial magnetometer data collected on ten wild Kalahari meerkats (Suricata suricatta), with annotated video recordings of each individual serving as groundtruth. Finally, we compare our results with accelerometer-based behaviour recognition.

RESULTS

The overall recognition accuracy of > 94% obtained with magnetometer data was found to be comparable to that achieved using accelerometer data. Interestingly, higher robustness to inter-individual variability in dynamic behaviour was achieved with the magnetometer, while the accelerometer was better at estimating posture.

CONCLUSIONS

Magnetometers were found to accurately identify common behaviours, and were particularly robust to dynamic behaviour recognition. The use of biomechanical considerations to summarise magnetometer data makes the hybrid scheme capable of accommodating data from either or both sensors within the same framework according to each sensor's strengths. This provides future studies with a method to assess the added benefit of using magnetometers for behaviour recognition.

Development of a gold-standard method for the identification of sedentary, light and moderate physical activities in older adults: Definitions for video annotation

OBJECTIVES

The development of a reliable method for the identification of sedentary, light and moderate physical activities in older adults. The method consists of a validated set of definitions for the identification of the initiation and termination of physical activities performed by older adult participants, video recorded during free-living and a laboratory setting.

DESIGN

Inter-rater reliability assessment in a fully crossed design.

METHODS

An iterative consensus process was used to define the initiation and termination of common activities of daily living. These definitions were then tested using videos recorded in two scenarios (1) by 9 raters who annotated a video recording, of a free-living protocol in a home environment, recorded in a first person view, using a body-worn camera and (2) by 7 raters who annotated a video recording, of older adults performing a semi-structured protocol in a living-lab environment, recorded in a third person view, using wall mounted cameras.

RESULTS

Inter-rater reliability was excellent for all items, with Krippendorff's alpha and Fleiss' kappa all above 0.84 and a percentage of agreement above 88%. All ICC(C,1) inter-rater values for the activity quantity and duration were all above 0.9.

CONCLUSIONS

This set of physical activity initiation and termination definitions offers independent researchers a gold standard method to allow for the consistent annotation of high-frequency video footage (25fps), in both a free-living and laboratory setting. When synchronised with body-worn or ambient sensors, this annotation will allow for the development and validation of physical activity classification systems to a higher resolution than before.

The utility of two interview-based physical activity questionnaires in healthy young adults: Comparison with accelerometer data

Background

Accurate assessment of physical activity is essential to determine the magnitude of the health-related benefits of regular physical activity. While physical activity questionnaires are easy to use, their accuracy in comparison to objective measures has been questioned. The purpose of the present study was to examine the utility of two interview-based questionnaires; a recently-developed instrument, the Simple Physical Activity Questionnaire (SIMPAQ), and the Seven Day-Physical Activity Recall (7DPAR).

Methods

Accelerometer data was collected in 72 university students (50% females). Telephone interviews were conducted to complete the SIMPAQ and the 7DPAR.

Results

Significant correlations (p < .001) were found between accelerometer-based moderate-to-vigorous physical activity (MVPA), the amount of self-reported moderate-to-vigorous exercise assessed via the SIMPAQ (rho = .49), and vigorous physical activity assessed via the 7DPAR (rho = .50). Exercise assessed via the SIMPAQ was significantly correlated with the vigorous physical activity score of the 7DPAR (rho = .56, p < .001). While participants needed three minutes less to complete the SIMPAQ (p < .001), participants tended to be more confident about the accuracy of the answers they provided on the 7DPAR (p < .01).

Conclusions

These two questionnaire measures of physical activity performed similarly in a healthy young adult sample. The SIMPAQ can be completed in 15 minutes, which could be an advantage in settings where time for physical activity assessment is limited.

A systematic literature review of reviews on techniques for physical activity measurement in adults: a DEDIPAC study

The links between increased participation in Physical Activity (PA) and improvements in health are well established. As this body of evidence has grown, so too has the search for measures of PA with high levels of methodological effectiveness (i.e. validity, reliability and responsiveness to change). The aim of this “review of reviews” was to provide a comprehensive overview of the methodological effectiveness of currently employed measures of PA, to aid researchers in their selection of an appropriate tool. A total of 63 review articles were included in this review, and the original articles cited by these reviews were included in order to extract detailed information on methodological effectiveness.

Self-report measures of PA have been most frequently examined for methodological effectiveness, with highly variable findings identified across a broad range of behaviours. The evidence-base for the methodological effectiveness of objective monitors, particularly accelerometers/activity monitors, is increasing, with lower levels of variability observed for validity and reliability when compared to subjective measures. Unfortunately, responsiveness to change across all measures and behaviours remains under-researched, with limited information available.

Other criteria beyond methodological effectiveness often influence tool selection, including cost and feasibility. However, researchers must be aware of the methodological effectiveness of any measure selected for use when examining PA. Although no “perfect” tool for the examination of PA in adults exists, it is suggested that researchers aim to incorporate appropriate objective measures, specific to the behaviours of interests, when examining PA in free-living environments.

Analysis of Optimal Sensor Positions for Activity Classification and Application on a Different Data Collection Scenario

This paper focuses on optimal sensor positioning for monitoring activities of daily living and investigates different combinations of features and models on different sensor positions, i.e., the side of the waist, front of the waist, chest, thigh, head, upper arm, wrist, and ankle. Nineteen features are extracted, and the feature importance is measured by using the Relief-F feature selection algorithm. Eight classification algorithms are evaluated on a dataset collected from young subjects and a dataset collected from elderly subjects, with two different experimental settings. To deal with different sampling rates, signals with a high data rate are down-sampled and a transformation matrix is used for aligning signals to the same coordinate system. The thigh, chest, side of the waist, and front of the waist are the best four sensor positions for the first dataset (young subjects), with average accuracy values greater than 96%. The best model obtained from the first dataset for the side of the waist is validated on the second dataset (elderly subjects). The most appropriate number of features for each sensor position is reported. The results provide a reference for building activity recognition models for different sensor positions, as well as for data acquired from different hardware platforms and subject groups.

Influence of cardiorespiratory fitness and physical activity levels on cardiometabolic risk factors during menopause transition: A MONET study

To determine the influence of cardiorespiratory fitness (hereafter “fitness”) and physical activity levels on cardiometabolic risk factors in premenopausal women going through the menopause transition. An ancillary study including 66 premenopausal women who participated to a 5-year observational, longitudinal study (2004 to 2009 in Ottawa) on the effects of menopause transition on body composition and cardiometabolic risk factors. Women underwent a graded exercise test on treadmill to measure peak oxygen uptake (VO₂ peak) at year 1 and 5 and physical activity levels were measured using accelerometers. Cardiometabolic risk factors included: waist circumference, fasting plasma lipids, glucose and insulin levels, HOMA-IR score, c-reactive protein, apolipoprotein B (apoB) and resting systolic and diastolic blood pressure. Change in fitness was not associated with changes in cardiometabolic risk factors. The changes in total physical activity levels on the other hand showed a significant negative association with apoB levels. Three-way linear mixed model repeated measures, showed lower values of waist circumference, fasting triglycerides, insulin levels, HOMA-IR score, apoB and diastolic blood pressure in women with a fitness ≥ 30.0 mlO₂ kg^− 1 min^− 1 compared to women with a fitness < 30.0 mlO₂ kg^− 1 min^− 1 (P < 0.05). However, only fasting triglycerides was lower in women with physical activity levels ≥ 770.0 Kcal/day (P < 0.05). Between fitness and physical activity levels, fitness was associated with more favorable values of cardiometabolic risk factors in women followed for 5 years during the menopause transition.

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Fitness and physical activity levels are independent predictors of CVD.

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Change in total physical activity levels was negatively association with apoB.

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Fitness was associated with more favorable values of cardiometabolic risk factors.

Energy depletion by diet or aerobic exercise alone: impact of energy deficit modality on appetite parameters

BACKGROUND

Millions of Americans attempt to lose weight each year, and it is unclear whether the modality of acute, tightly controlled energy depletions can differently affect appetite parameters and olfaction.

OBJECTIVE

The objectives were to examine how the modality of an acute 3-d isocaloric 25% energy depletion by dieting alone or by aerobic exercise alone differently affects appetite and appetite-related hormones, ad libitum feeding, food reward (snack points), and olfaction.

DESIGN

Ten male participants with a mean ± SD age of 23.7 ± 5.1 y and an initial mean ± SD body weight of 83.2 ± 11.5 kg participated in this randomized crossover design. Baseline measurement [day 1 of the control condition (CON1)] was performed and repeated 3 d later [day 4 of the control condition (CON4)], after which randomization was applied to the order of the 2 experimental conditions: 25% daily needs energy deficits induced by diet only (DIET) and by exercise only (EX) and tested before [day 1 of DIET (DIET1) and day 1 of EX (EX1)] and after 3 d [day 4 of DIET (DIET4) and day 4 of EX (EX4)] of the intervention. Body weight, leptin and ghrelin concentrations, relative-reinforcing value of food, and olfaction were measured at days 1 and 4. Body composition (dual-energy X-ray absorptiometry), ad libitum energy intake (EI; buffet), and palatability (visual analog scale) were measured only at day 4.

RESULTS

Relative to CON4, EI (P= 0.001), palatability (P= 0.01), and odor threshold (P= 0.05) were higher at DIET4; relative to CON4, palatability (P= 0.03) was higher at EX4. Compared with EX4, EI was higher for DIET4 (P= 0.006). Relative to CON4, snack points earned were higher at DIET4 (P= 0.03) and EX4 (P= 0.001); more snack points were earned at EX4 relative to DIET4 (P= 0.001).

CONCLUSIONS

Compared with the control condition, DIET represented a greater acute challenge to appetite regulation than EX, as demonstrated by greater appetite and ad libitum EI. This study confirms that compared with depletions by exercise alone, acute caloric restriction results in rapid changes in appetite that result in compensatory eating, which may initially dissuade potential success in weight-loss efforts. This trial was registered at clinicaltrials.gov as NCT02653378.

Effect of wearable sensor dynamics on physical activity estimates: A comparison between SCI vs. healthy individuals

Accuracy of physical activity estimates predicted by activity monitoring technologies may be affected by device location, analysis algorithms, type of technology (i.e. wearable/stickable) and population demographics (disability) being studied. Consequently, the main purpose of this investigation was to study such sensor dynamics (i.e. effect of device location, type and population demographics on energy expenditure estimates) of two commercial activity monitors. It was hypothesized that device location, population studied (disability), choice of proprietary algorithm and type of technology used will significantly impact the accuracy of the predicted physical activity metrics. 10 healthy controls and eight individuals with spinal cord injury (SCI) performed structured activities in a laboratory environment. All participants wore, (i) three ActiGraph-G3TX's one each on their wrist, waist & ankle, (ii) a stickable activity monitor (Metria-IH1) on their upper-arm and (3) a Cosmed-K4B² metabolic unit, while performing sedentary (lying), low intensity (walk 50 steps at self-speed) and vigorous activity (a 6 minute walk test). To validate the hypothesis, the energy expenditures (EE) predicted by ActiGraph-GT3X and Metria-IH1 were benchmarked with estimated EE per Cosmed K4B² metabolic unit. To verify the step count accuracy predicted by ActiGraph-GT3X's and Metria-IH1, the manually calculated step count during the low intensity activity were compared to estimates from both devices. Results suggest that Metria-IH1 out-performed ActiGraph-GT3X in estimating EE during sedentary activity in both groups. The device location and population demographics, significantly affected the accuracy of predicted estimates. In conclusion, selecting activity monitor locations, analysis algorithm and choice of technology plays based on the movement threshold of population being studied can pave a better way for reliable healthcare decisions and data analytics in population with SCI.

Inertial Sensor Technology for Elite Swimming Performance Analysis: A Systematic Review

Technical evaluation of swimming performance is an essential factor of elite athletic preparation. Novel methods of analysis, incorporating body worn inertial sensors (i.e., Microelectromechanical systems, or MEMS, accelerometers and gyroscopes), have received much attention recently from both research and commercial communities as an alternative to video-based approaches. This technology may allow for improved analysis of stroke mechanics, race performance and energy expenditure, as well as real-time feedback to the coach, potentially enabling more efficient, competitive and quantitative coaching. The aim of this paper is to provide a systematic review of the literature related to the use of inertial sensors for the technical analysis of swimming performance. This paper focuses on providing an evaluation of the accuracy of different feature detection algorithms described in the literature for the analysis of different phases of swimming, specifically starts, turns and free-swimming. The consequences associated with different sensor attachment locations are also considered for both single and multiple sensor configurations. Additional information such as this should help practitioners to select the most appropriate systems and methods for extracting the key performance related parameters that are important to them for analysing their swimmers' performance and may serve to inform both applied and research practices.

Step detection using multi- versus single tri-axial accelerometer-based systems

Multiple sensors are often considered necessary for increased step count accuracy. However, subject adherence to device-wear increases using a minimal number of activity monitors (AMs). The study aims were to determine and compare the validity of using multiple AMs versus a single AM to detect steps by comparison to video using a modification of an algorithm previously developed for a four-accelerometer AM system capable, unlike other algorithms, of accurate step detection for gait velocities as low as 0.1 m s(-1). Twelve healthy adults wore ankle, thigh and waist AMs while performing walking/jogging trials at gait velocities from 0.1-4.8 m s(-1) and a simulated free-living dynamic activities protocol. Nineteen older adults wore ankle and waist AMs while walking at velocities from 0.5-2.0 m s(-1). As little as one AM (thigh or waist) accurately detected steps for velocities  >0.5 m s(-1). A single ankle AM accurately detected steps for velocities  ⩾0.1 m s(-1). Only the thigh AM could not accurately detect steps during the dynamic activities. Only the thigh-ankle combination or single waist AM could accurately distinguish between walking and jogging steps. These laboratory-based results suggest that the presented algorithm can accurately detect steps in a free-living environment using only one ankle or waist AM.

GT3X+ accelerometer placement affects the reliability of step-counts measured during running and pedal-revolution counts measured during bicycling

Accelerometers provide a measure of step-count. Reliability and validity of step-count and pedal-revolution count measurements by the GT3X+ accelerometer, placed at different anatomical locations, is absent in the literature. The purpose of this study was to investigate the reliability and validity of step and pedal-revolution counts produced by the GT3X+ placed at different anatomical locations during running and bicycling. Twenty-two healthy adults (14 men and 8 women) completed running and bicycling activity bouts (5 minutes each) while wearing 6 accelerometers: 2 each at the waist, thigh and shank. Accelerometer and video data were collected during activity. Excellent reliability and validity were found for measurements taken from accelerometers mounted at the waist and shank during running (Reliability: intraclass correlation (ICC) ≥ 0.99; standard error of measurement (SEM) ≤1.0 steps;

VALIDITY

Pearson ≥ 0.99) and at the thigh and shank during bicycling (Reliability: ICC ≥ 0.99; SEM ≤1.0 revolutions;

VALIDITY

Pearson ≥ 0.99). Excellent reliability was found between measurements taken at the waist and shank during running (ICC ≥ 0.98; SEM ≤1.6 steps) and between measurements taken at the thigh and shank during bicycling (ICC ≥ 0.99; SEM ≤1.0 revolutions). These data suggest that the GT3X+ can be used for measuring step-count during running and pedal-revolution count during bicycling. Only shank placement is recommended for both activities.

Physical Activity Capture Technology With Potential for Incorporation Into Closed-Loop Control for Type 1 Diabetes

Physical activity is an important determinant of glucose variability in type 1 diabetes (T1D). It has been incorporated as a nonglucose input into closed-loop control (CLC) protocols for T1D during the last 4 years mainly by 3 research groups in single center based controlled clinical trials involving a maximum of 18 subjects in any 1 study. Although physical activity data capture may have clinical benefit in patients with T1D by impacting cardiovascular fitness and optimal body weight achievement and maintenance, limited number of such studies have been conducted to date. Clinical trial registries provide information about a single small sample size 2 center prospective study incorporating physical activity data input to modulate closed-loop control in T1D that are seeking to build on prior studies. We expect an increase in such studies especially since the NIH has expanded support of this type of research with additional grants starting in the second half of 2015. Studies (1) involving patients with other disorders that have lasted 12 weeks or longer and tracked physical activity and (2) including both aerobic and resistance activity may offer insights about the user experience and device optimization even as single input CLC heads into real-world clinical trials over the next few years and nonglucose input is introduced as the next advance.

Validity and practical utility of accelerometry for the measurement of in-hand physical activity in horses

Background

Accelerometers are valid, practical and reliable tools for the measurement of habitual physical activity (PA). Quantification of PA in horses is desirable for use in research and clinical settings. The objective of this study was to evaluate a triaxial accelerometer for objective measurement of PA in the horse by assessment of their practical utility and validity.

Horses were recruited to establish both the optimal site of accelerometer attachment and questionnaire designed to explore owner acceptance. Validity and cut-off values were obtained by assessing PA at various gaits. Validation study- 20 horses wore the accelerometer while being filmed for 10 min each of rest, walking and trotting and 5 mins of canter work. Practical utility study- five horses wore accelerometers on polls and withers for 18 h; compliance and relative data losses were quantified.

Results

Accelerometry output differed significantly between the four PA levels (P < 0•001) for both wither and poll placement. For withers placement, ROC analyses found optimal sensitivity and specificity at a cut-off of <47 counts per minute (cpm) for rest (sensitivity 99.5 %, specificity 100 %), 967–2424 cpm for trotting (sensitivity 96.7 %, specificity 100 %) and ≥2425 cpm for cantering (sensitivity 96.0 %, specificity 97.0 %). Attachment at the poll resulted in optimal sensitivity and specificity at a cut-off of <707 counts per minute (cpm) for rest (sensitivity 97.5 %, specificity 99.6 %), 1546–2609 cpm for trotting (sensitivity 90.33 %, specificity 79.25 %) and ≥2610 cpm for cantering (sensitivity 100 %, specificity 100 %) In terms of practical utility, accelerometry was well tolerated and owner acceptance high.

Conclusion

Accelerometry data correlated well with varying levels of in-hand equine activity. The use of accelerometers is a valid method for objective measurement of controlled PA in the horse.

Acute Effects of a Therapeutic Mobility Device on Physical Activity and Heart Rate in Children With Down Syndrome

PURPOSE

The purpose of this feasibility study was to provide an opportunity to increase physical activity (PA) and heart rate (HR) for children with Down syndrome (DS) during unstructured group exercise utilizing a riding device called the Power Pumper®.

METHOD

Twenty-four children aged 5 to 7 years old participated in this case-control study, including 12 children with DS and 12 children without DS. Those without DS participated as age-matched controls. A 30-min unstructured PA session utilizing the Power Pumper was provided to both groups on 2 occasions. HR and PA were measured at baseline and during both sessions.

RESULTS

For children with DS, findings revealed a statistically significant increase in time spent in moderate-to-vigorous PA (MVPA), F(1, 15) = 16.503, p < .010, ES = 0.76, and a nonsignificant increase in HR (ES = 0.41) when comparing exercise session performance to baseline. For children without DS, findings revealed statistically significant increases in time spent in MVPA, F(1, 15) = 73.604, p < .010, ES = 0.94, and HR, F(1, 22) = 34.634, p < .010, ES = 0.69, between exercise and baseline. Total MVPA approached the recommended 60 min following device use. PA and HR differences between baseline and exercise were greater in magnitude for children without DS.

CONCLUSION

By participating in unstructured exercise in a social environment using the Power Pumper, children with DS engaged in higher-intensity PA accompanied by a nonsignificant physiological response in HR. These outcomes support PA guidelines recommended by the National Association for Sport and Physical Education. This device supports 1 option for achieving 60 min of MVPA daily.

Influence of accelerometer type and placement on physical activity energy expenditure prediction in manual wheelchair users

PURPOSE

To assess the validity of two accelerometer devices, at two different anatomical locations, for the prediction of physical activity energy expenditure (PAEE) in manual wheelchair users (MWUs).

METHODS

Seventeen MWUs (36 ± 10 yrs, 72 ± 11 kg) completed ten activities; resting, folding clothes, propulsion on a 1% gradient (3,4,5,6 and 7 km·hr-1) and propulsion at 4km·hr-1 (with an additional 8% body mass, 2% and 3% gradient) on a motorised wheelchair treadmill. GT3X+ and GENEActiv accelerometers were worn on the right wrist (W) and upper arm (UA). Linear regression analysis was conducted between outputs from each accelerometer and criterion PAEE, measured using indirect calorimetry. Subsequent error statistics were calculated for the derived regression equations for all four device/location combinations, using a leave-one-out cross-validation analysis.

RESULTS

Accelerometer outputs at each anatomical location were significantly (p < .01) associated with PAEE (GT3X+-UA; r = 0.68 and GT3X+-W; r = 0.82. GENEActiv-UA; r = 0.87 and GENEActiv-W; r = 0.88). Mean ± SD PAEE estimation errors for all activities combined were 15 ± 45%, 14 ± 50%, 3 ± 25% and 4 ± 26% for GT3X+-UA, GT3X+-W, GENEActiv-UA and GENEActiv-W, respectively. Absolute PAEE estimation errors for devices varied, 19 to 66% for GT3X+-UA, 17 to 122% for GT3X+-W, 15 to 26% for GENEActiv-UA and from 17.0 to 32% for the GENEActiv-W.

CONCLUSION

The results indicate that the GENEActiv device worn on either the upper arm or wrist provides the most valid prediction of PAEE in MWUs. Variation in error statistics between the two devices is a result of inherent differences in internal components, on-board filtering processes and outputs of each device.

Using accelerometry to quantify deceleration during a high-intensity soccer turning manoeuvre

Abstract The mechanics of cutting movements have been investigated extensively, but few studies have considered the rapid deceleration phase prior to turning which has been linked to muscle damage. This study used accelerometry to examine the influence of turning intensity on the last three steps of a severe turn. Ten soccer players performed 135° "V" cuts at five different intensities. Resultant decelerations were recorded from a trunk-mounted tri-axial accelerometer. Lower limb kinematics and ground reaction forces (GRF) from the pivot foot-ground contact (FGC) were also monitored. Average peak trunk decelerations were larger at the two preceding steps (4.37 ± 0.12 g and 4.58 ± 0.11 g) compared to the PIVOT step (4.10 ± 0.09 g). Larger peak joint flexion angular velocities were observed at PRE step (ankle: 367 ± 192 deg.s^-1; knee 493 ± 252  deg.s^-1) compared to PIVOT step (ankle 255 ± 183 deg.s^-1; knee 377 ± 229 deg.s^-1). Turn intensity did not influence peak GRF at PIVOT step. This study highlights the importance of steps prior to turning and their high-frequency loading characteristics. It is suggested that investigations of lower limb loading during turning should include this deceleration phase and not focus solely on pivot FGC.

Which activity monitor to use? Validity, reproducibility and user friendliness of three activity monitors

BACKGROUND

Health is associated with amount of daily physical activity. Recently, the identification of sedentary time as an independent factor, has gained interest. A valid and easy to use activity monitor is needed to objectively investigate the relationship between physical activity, sedentary time and health. We compared validity and reproducibility of physical activity measurement and posture identification of three activity monitors, as well as user friendliness.

METHODS

Healthy volunteers wore three activity monitors simultaneously: ActivPAL3, ActiGraphGT3X and CAM. Data were acquired under both controlled (n = 5) and free-living conditions (n = 9). The controlled laboratory measurement, that included standardized walking intensity and posture allocation, was performed twice. User friendliness was evaluated with a questionnaire. Posture classification was compared with direct observation (controlled measurement) and with diaries (free living). Accelerometer intensity accuracy was tested by correlations with walking speed. User friendliness was compared between activity monitors.

RESULTS

Reproducibility was at least substantial in all monitors. The difference between the two CAM measurements increased with walking intensity. Amount of correct posture classification by ActivPAL3 was 100.0% (kappa 0.98), 33.9% by ActiGraphGT3X (kappa 0.29) and 100.0% by CAM (kappa 0.99). Correlations between accelerometer intensity and walking speed were 0.98 for ActivPAL3, 1.00 for ActiGraphGT3X and 0.98 for CAM. ICCs between activity monitors and diary were 0.98 in ActivPAL3, 0.59 and 0.96 in ActiGraphGT3X and 0.98 in CAM. ActivPAL3 and ActiGraphGT3X had higher user friendliness scores than the CAM.

CONCLUSIONS

The ActivPAL3 is valid, reproducible and user friendly. The posture classification by the ActiGraphGT3X is not valid, but reflection of walking intensity and user friendliness are good. The CAM is valid; however, reproducibility at higher walking intensity and user friendliness might cause problems. Further validity studies in free living are recommended.

Assessment of physical activity and energy expenditure: an overview of objective measures

The ability to assess energy expenditure (EE) and estimate physical activity (PA) in free-living individuals is extremely important in the global context of non-communicable diseases including malnutrition, overnutrition (obesity), and diabetes. It is also important to appreciate that PA and EE are different constructs with PA defined as any bodily movement that results in EE and accordingly, energy is expended as a result of PA. However, total energy expenditure, best assessed using the criterion doubly labeled water (DLW) technique, includes components in addition to physical activity energy expenditure, namely resting energy expenditure and the thermic effect of food. Given the large number of assessment techniques currently used to estimate PA in humans, it is imperative to understand the relative merits of each. The goal of this review is to provide information on the utility and limitations of a range of objective measures of PA and their relationship with EE. The measures discussed include those based on EE or oxygen uptake including DLW, activity energy expenditure, physical activity level, and metabolic equivalent; those based on heart rate monitoring and motion sensors; and because of their widespread use, selected subjective measures.

Consistency of gait characteristics as determined from acceleration data collected at different trunk locations

Estimates of gait characteristics may suffer from errors due to discrepancies in accelerometer location. This is particularly problematic for gait measurements in daily life settings, where consistent sensor positioning is difficult to achieve. To address this problem, we equipped 21 healthy adults with tri-axial accelerometers (DynaPort MiniMod, McRoberts) at the mid and lower lumbar spine and anterior superior iliac spine (L2, L5 and ASIS) while continuously walking outdoors back and forth (20 times) over a distance of 20 m, including turns. We compared 35 gait characteristics between sensor locations by absolute agreement intra-class correlations (2, 1; ICC). We repeated these analyses after applying a new method for off-line sensor realignment providing a unique definition of the vertical and, by symmetry optimization, the two horizontal axes. Agreement between L2 and L5 after realignment was excellent (ICC>0.9) for stride time and frequency, speed and their corresponding variability and good (ICC>0.7) for stride regularity, movement intensity, gait symmetry and smoothness and for local dynamic stability. ICC values benefited from sensor realignment. Agreement between ASIS and the lumbar locations was less strong, in particular for gait characteristics like symmetry, smoothness, and local dynamic stability (ICC generally<0.7). Unfortunately, this lumbar-ASIS agreement did not benefit consistently from sensor realignment. Our findings show that gait characteristics are robust against limited repositioning error of sensors at the lumbar spine, in particular if our off-line realignment is applied. However, larger positioning differences (from lumbar positions to ASIS) yield less consistent estimates and should hence be avoided.

Optimal sensor placement for measuring physical activity with a 3D accelerometer

Accelerometer-based activity monitors are popular for monitoring physical activity. In this study, we investigated optimal sensor placement for increasing the quality of studies that utilize accelerometer data to assess physical activity. We performed a two-staged study, focused on sensor location and type of mounting. Ten subjects walked at various walking speeds on a treadmill, performed a deskwork protocol, and walked on level ground, while simultaneously wearing five ProMove2 sensors with a snug fit on an elastic waist belt. We found that sensor location, type of activity, and their interaction-effect affected sensor output. The most lateral positions on the waist belt were the least sensitive for interference. The effect of mounting was explored, by making two subjects repeat the experimental protocol with sensors more loosely fitted to the elastic belt. The loose fit resulted in lower sensor output, except for the deskwork protocol, where output was higher. In order to increase the reliability and to reduce the variability of sensor output, researchers should place activity sensors on the most lateral position of a participant's waist belt. If the sensor hampers free movement, it may be positioned slightly more forward on the belt. Finally, sensors should be fitted tightly to the body.

Light physical activity is a better determinant of lower adiposity during the menopausal transition

OBJECTIVE

To investigate the relationship between time spent performing physical activity (PA) and adiposity across the menopausal transition.

METHODS

Body weight and body composition were analyzed in 65 women (47-54 years old; body mass index 23.2 ± 2.4 kg/m(2)) in a 5-year prospective study. Time spent in PA of varying intensities (sedentary, light, moderate and vigorous) was determined from 7-day accelerometer measurement and energy intake with a 7-day food diary.

RESULTS

Significant negative correlations were observed between the time spent in light-intensity PA and fat mass (FM) (r = -0.38, p < 0.005), central FM (r = -0.36, p < 0.005), peripheral FM (r = -0.33, p < 0.01), and percent body fat (r = -0.42, p < 0.001) at year 1, respectively. No significant correlations were noted between measures of adiposity and time spent performing either moderate or vigorous PA. Analyses using tertiles of time spent in light PA at year 1 showed that FM (20.7 ± 4.0 vs. 20.3 ± 6.6 vs. 16.6 ± 4.6 kg, p < 0.05), central FM (10.1 ± 2.6 vs. 10.0 ± 3.8 vs. 7.8 ± 2.4 kg; p < 0.05) and percent body fat (34.5 ± 5.1 vs. 32.2 ± 7.7 vs. 28.1 ± 6.2%, p < 0.01) were all significantly lower in women in the highest tertile. These differences remained significant after covariate analyses using time spent in moderate- and high-intensity PA and total energy intake. Finally, lower levels of FM, percent body fat, central and peripheral FM persisted in women who spent more time in light PA (highest tertiles) over the 5-year follow-up.

CONCLUSION

Our results suggest that the time spent performing light PA may have a greater impact on adiposity than moderate and/or vigorous PA, an observation independent of the menopausal status.

Separating movement and gravity components in an acceleration signal and implications for the assessment of human daily physical activity

Introduction

Human body acceleration is often used as an indicator of daily physical activity in epidemiological research. Raw acceleration signals contain three basic components: movement, gravity, and noise. Separation of these becomes increasingly difficult during rotational movements. We aimed to evaluate five different methods (metrics) of processing acceleration signals on their ability to remove the gravitational component of acceleration during standardised mechanical movements and the implications for human daily physical activity assessment.

Methods

An industrial robot rotated accelerometers in the vertical plane. Radius, frequency, and angular range of motion were systematically varied. Three metrics (Euclidian norm minus one [ENMO], Euclidian norm of the high-pass filtered signals [HFEN], and HFEN plus Euclidean norm of low-pass filtered signals minus 1 g [HFEN₊]) were derived for each experimental condition and compared against the reference acceleration (forward kinematics) of the robot arm. We then compared metrics derived from human acceleration signals from the wrist and hip in 97 adults (22–65 yr), and wrist in 63 women (20–35 yr) in whom daily activity-related energy expenditure (PAEE) was available.

Results

In the robot experiment, HFEN₊ had lowest error during (vertical plane) rotations at an oscillating frequency higher than the filter cut-off frequency while for lower frequencies ENMO performed better. In the human experiments, metrics HFEN and ENMO on hip were most discrepant (within- and between-individual explained variance of 0.90 and 0.46, respectively). ENMO, HFEN and HFEN₊ explained 34%, 30% and 36% of the variance in daily PAEE, respectively, compared to 26% for a metric which did not attempt to remove the gravitational component (metric EN).

Conclusion

In conclusion, none of the metrics as evaluated systematically outperformed all other metrics across a wide range of standardised kinematic conditions. However, choice of metric explains different degrees of variance in daily human physical activity.

Effects of the menopausal transition on energy expenditure: a MONET Group Study

Objectives

Factors that influence weight gain during the menopausal transition are not fully understood. The purpose of this study was to investigate changes in energy expenditure (EE) across the menopausal transition.

Methods

One hundred and two premenopausal women (age: 49.9 ± 1.9 yrs; BMI: 23.3 ± 2.2 kg/m²) were followed for 5 years. Body composition (DXA), physical activity EE (accelerometer), resting EE and thermic effect of food (indirect calorimetry) were measured annually.

Results

Total EE decreased significantly over time in postmenopausal women (P < 0.05), which was mostly due to a decrease in physical activity EE (P < 0.05). Although average resting EE remained stable over time in postmenopausal women, a significant increase, over the 5-year period, was noted in women who were in the menopausal transition by year 5 (P < 0.05). Finally, the time spent in moderate physical activity decreased and the time spent in sedentary physical activity increased during the menopausal transition (P < 0.05).

Conclusion

These results suggest that menopausal transition is accompanied with a decline in EE mainly characterized by a decrease in physical activity EE and a shift to a more sedentary lifestyle.

On higher ground: how well can dynamic body acceleration determine speed in variable terrain?

Introduction

Animal travel speed is an ecologically significant parameter, with implications for the study of energetics and animal behaviour. It is also necessary for the calculation of animal paths by dead-reckoning. Dead-reckoning uses heading and speed to calculate an animal’s path through its environment on a fine scale. It is often used in aquatic environments, where transmission telemetry is difficult. However, its adoption for tracking terrestrial animals is limited by our ability to measure speed accurately on a fine scale. Recently, tri-axial accelerometers have shown promise for estimating speed, but their accuracy appears affected by changes in substrate and surface gradients. The purpose of the present study was to evaluate four metrics of acceleration; Overall dynamic body acceleration (ODBA), vectorial dynamic body acceleration (VDBA), acceleration peak frequency and acceleration peak amplitude, as proxies for speed over hard, soft and inclined surfaces, using humans as a model species.

Results

A general linear model (GLM) showed a significant difference in the relationships between the metrics and speed depending on substrate or surface gradient. When the data from all surface types were considered together, VeDBA had the highest coefficient of determination.

Conclusions

All of the metrics showed some variation in their relationship with speed according to the surface type. This indicates that changes in the substrate or surface gradient during locomotion by animals would produce errors in speed estimates, and also in dead-reckoned tracks if they were calculated from speeds based entirely on a priori calibrations. However, we describe a method by which the relationship between acceleration metrics and speed can be corrected ad hoc, until tracks accord with periodic ground truthed positions, obtained via a secondary means (e.g. VHF or GPS telemetry). In this way, dead-reckoning provides a means to obtain fine scale movement data for terrestrial animals, without the need for additional data on substrate or gradient.

The effect of the menopausal transition on body composition and cardiometabolic risk factors: a Montreal-Ottawa New Emerging Team group study

OBJECTIVE

Cardiovascular disease is the first cause of mortality in women in North America. The risk of cardiovascular disease increases sharply after middle age in women, especially after menopause. The aim was to investigate changes in body composition and cardiometabolic profile throughout the menopausal transition.

METHODS

This was a 5-year observational, longitudinal study on the menopausal transition. The study included 102 premenopausal women at baseline (age, 49.9 ± 1.9 y; body mass index, 23.3 ± 2.2 kg/m). Outcome measures include menopause status, body composition by dual-energy x-ray absorptiometry (total fat mass [FM], trunk FM, and total fat-free mass), waist circumference, visceral and abdominal subcutaneous fat, fasting glucose and insulin levels, homeostasis model assessment of insulin resistance, plasma lipid levels (triglycerides, total cholesterol, and high- and low-density lipoprotein cholesterol), and resting blood pressure.

RESULTS

Repeated-measure analyses revealed significant increases for FM, percentage FM, trunk FM, visceral fat, plasma fasting glucose, and high-density lipoprotein cholesterol (0.05 > P < 0.01) and a significant decrease for plasma glucose levels after follow-up. Those who were in perimenopause or postmenopause by year 3 of the study showed a significant increase in visceral fat (P < 0.01) compared with baseline. Despite some significant changes in the metabolic profile among the menopause statuses, the women did not show any cardiometabolic deterioration by the end of the study.

CONCLUSIONS

Our results suggest that changes in body composition and fat distribution can occur in nonobese women as they go through the menopausal transition. However, these changes were not accompanied by cardiometabolic deteriorations in the present study.

Wrist-worn accelerometers in assessment of energy expenditure during intensive training

We assessed the ability of the Polar activity recorder (AR) to measure energy expenditure (EE) during military training. Twenty-four voluntary male conscripts participated in the study and wore an AR on the non-dominant wrist 24 h a day for 7 d. The AR analyzed and stored the frequency of hand movements (f_hand) into memory at 1 min intervals. The relationship between f_hand and EE was studied over a 7 d period of military training using the doubly labeled water (DLW) technique. In addition, the relationship between f_hand and EE was analyzed during walking and running on a treadmill with an indirect calorimeter (IC), and f_hand was measured during a supervised 45 min field march test where the conscripts carried combat gear. EE was expressed as physical activity level (PAL), total energy expenditure (TEE), and activity-induced energy expenditure adjusted for body mass (AEE/BM). Over the 7 d period, f_hand alone explained 46% of inter-individual variation in PAL(DLW). After inclusion of body height and mass in the model used to predict PAL(DLW) from f_hand, a very high positive correlation and a low standard error of estimate (SEE) were observed between the AR and DLW techniques: for TEE r = 0.86 (p < 0.001), the SEE was 6.3%, and for AEE/BM r = 0.84 (p < 0.001), the SEE was 12.8%. In the treadmill exercise, f_hand correlated highly with PAL(IC) (r = 0.97 ± 0.02). In the 45 min field march test, the AR measured similar f_hand as on the treadmill at the same speed. In conclusion, the wrist-worn AR can be regarded as a reliable and valid method for assessing EE during intensive training.

Energy expenditure estimation during normal ambulation using triaxial accelerometry and barometric pressure

Energy expenditure (EE) is an important parameter in the assessment of physical activity. Most reliable techniques for EE estimation are too impractical for deployment in unsupervised free-living environments; those which do prove practical for unsupervised use often poorly estimate EE when the subject is working to change their altitude by walking up or down stairs or inclines. This study evaluates the augmentation of a standard triaxial accelerometry waist-worn wearable sensor with a barometric pressure sensor (as a surrogate measure for altitude) to improve EE estimates, particularly when the subject is ascending or descending stairs. Using a number of features extracted from the accelerometry and barometric pressure signals, a state space model is trained for EE estimation. An activity classification algorithm is also presented, and this activity classification output is also investigated as a model input parameter when estimating EE. This EE estimation model is compared against a similar model which solely utilizes accelerometry-derived features. A protocol (comprising lying, sitting, standing, walking, walking up stairs, walking down stairs and transitioning between activities) was performed by 13 healthy volunteers (8 males and 5 females; age: 23.8 ± 3.7 years; weight: 70.5 ± 14.9 kg), whose instantaneous oxygen uptake was measured by means of an indirect calorimetry system (K4b(2), COSMED, Italy). Activity classification improves from 81.65% to 90.91% when including barometric pressure information; when analyzing walking activities alone the accuracy increases from 70.23% to 98.54%. Using features derived from both accelerometry and barometry signals, combined with features relating to the activity classification in a state space model, resulted in a VO(2) estimation bias of -0.00 095 and precision (1.96SD) of 3.54 ml min(-1) kg(-1). Using only accelerometry features gives a relatively worse performance, with a bias of -0.09 and precision (1.96SD) of 5.99 ml min(-1) kg(-1), with the largest errors due to an underestimation of VO(2) when walking up stairs.

Estimation of walking energy expenditure by using support vector regression

This paper develops a new predictor of walking energy expenditure from wireless measurements of body movements using triaxial accelerometers. Reliable data were collected from repeated walking experiments in different conditions on a treadmill with simultaneous measurement of expired oxygen and carbon dioxide. Support vector regression, a powerful non-linear regression method, was used to process and model the data. This novel processing method sets this investigation apart from existing papers. Good results were achieved in the robust estimation of walking related energy expenditure from a number of variables derived from triaxial accelerometer and treadmill speed.

Walking pattern classification and walking distance estimation algorithms using gait phase information

This paper presents a walking pattern classification and a walking distance estimation algorithm using gait phase information. A gait phase information retrieval algorithm was developed to analyze the duration of the phases in a gait cycle (i.e., stance, push-off, swing, and heel-strike phases). Based on the gait phase information, a decision tree based on the relations between gait phases was constructed for classifying three different walking patterns (level walking, walking upstairs, and walking downstairs). Gait phase information was also used for developing a walking distance estimation algorithm. The walking distance estimation algorithm consists of the processes of step count and step length estimation. The proposed walking pattern classification and walking distance estimation algorithm have been validated by a series of experiments. The accuracy of the proposed walking pattern classification was 98.87%, 95.45%, and 95.00% for level walking, walking upstairs, and walking downstairs, respectively. The accuracy of the proposed walking distance estimation algorithm was 96.42% over a walking distance.

Differences in walking pattern during 6-min walk test between patients with COPD and healthy subjects

Background

To date, detailed analyses of walking patterns using accelerometers during the 6-min walk test (6MWT) have not been performed in patients with chronic obstructive pulmonary disease (COPD). Therefore, it remains unclear whether and to what extent COPD patients have an altered walking pattern during the 6MWT compared to healthy elderly subjects.

Methodology/Principal Findings

79 COPD patients and 24 healthy elderly subjects performed the 6MWT wearing an accelerometer attached to the trunk. The accelerometer features (walking intensity, cadence, and walking variability) and subject characteristics were assessed and compared between groups. Moreover, associations were sought with 6-min walk distance (6MWD) using multiple ordinary least squares (OLS) regression models. COPD patients walked with a significantly lower walking intensity, lower cadence and increased walking variability compared to healthy subjects. Walking intensity and height were the only two significant determinants of 6MWD in healthy subjects, explaining 85% of the variance in 6MWD. In COPD patients also age, cadence, walking variability measures and their interactions were included were significant determinants of 6MWD (total variance in 6MWD explained: 88%).

Conclusions/Significance

COPD patients have an altered walking pattern during 6MWT compared to healthy subjects. These differences in walking pattern partially explain the lower 6MWD in patients with COPD.

Accelerometer-based on-body sensor localization for health and medical monitoring applications

In this paper, we present a technique to recognize the position of sensors on the human body. Automatic on-body device localization ensures correctness and accuracy of measurements in health and medical monitoring systems. In addition, it provides opportunities to improve the performance and usability of ubiquitous devices. Our technique uses accelerometers to capture motion data to estimate the location of the device on the user's body, using mixed supervised and unsupervised time series analysis methods. We have evaluated our technique with extensive experiments on 25 subjects. On average, our technique achieves 89% accuracy in estimating the location of devices on the body. In order to study the feasibility of classification of left limbs from right limbs (e.g., left arm vs. right arm), we performed analysis, based of which no meaningful classification was observed. Personalized ultraviolet monitoring and wireless transmission power control comprise two immediate applications of our on-body device localization approach. Such applications, along with their corresponding feasibility studies, are discussed.

Transient and steady state estimation of human oxygen uptake based on noninvasive portable sensor measurements

The main motivation of this study is to establish an ambulatory cardio-respiratory analysis system for the monitoring and evaluation of exercise and regular daily physical activity. We explored the estimation of oxygen uptake by using noninvasive portable sensors. These sensors are easy to use but may suffer from malfunctions under free living environments. A promising solution is to combine sensors with different measuring mechanisms to improve both reliability and accuracy of the estimation results. For this purpose, we selected a wireless heart rate sensor and a tri-axial accelerometer to form a complementary sensor platform. We analyzed the relationship between oxygen uptake measured by gas analysis and data collected from the simple portable sensors using multivariable nonlinear modeling approaches. It was observed that the resulting nonlinear multivariable model could not only achieve a better estimate compared with single input single output models, but also had greater potential to improve reliability.

Energy expenditure estimation using triaxial accelerometry and barometric pressure measurement

Energy expenditure (EE) is a parameter of great relevance in studies involving the assessment of physical activity. However, most reliable techniques for EE estimation are impractical for use in free-living environments, and those which are practically useful often poorly track EE when the subject is working to change their altitude, for example when ascending or descending stairs or slopes. The aim of this study is to evaluate the utility of adding barometric pressure related features, as a surrogate measure for altitude, to existing accelerometry related features to estimate the subject's EE. The EE estimation system described is based on a triaxial accelerometer (triax) and a barometric pressure sensor. The device is wireless, with Bluetooth connectivity for data retrieval, and is mounted at the subject's waist. Using a number of features extracted from the triax and barometric pressure signals, a linear model is trained for EE estimation. This EE estimation model is compared to its counterpart, which solely utilizes accelerometry signals. A protocol (comprising lying, sitting, standing, walking phases) was performed by 13 healthy volunteers (8 male and 5 female; age: 23.8 ± 3.7 years; weight: 70.5 ± 14.9 kg), whose instantaneous oxygen uptake was measured by means of an indirect calorimetry system. The model incorporating barometric pressure information estimated the oxygen uptake with the lowest mean square error of 4.5 ± 1.7 (mlO(2).min(-1).kg(-1))(2), in comparison to 7.1 ± 2.3 (mlO(2).min(-1).kg(-1))(2) using only accelerometry-based features.

Effects of BMI and abdominal volume on the accuracy of step count obtained from a tri-axial accelerometer

Accelerometers are widely accepted as practical wearable devices capable of measuring and assessing physical activity. These devices may, however, be subject to errors which could impact on their ability to acquire an accurate step count. A limited number of studies have examined the effects of body mass index (BMI) on the accuracy of accelerometers functioning as step counters. It has been suggested that BMI may not be the best indicator of adiposity. The aim of the present study was to assess the effects of BMI and abdominal volume on the accuracy of a step count obtained from a tri-axial accelerometer. Accelerometers were placed directly onto the skin at the chest, waist and lower back of 12 participants. Participants then walked on a motorized treadmill at 0.89 m/s and 1.34 m/s. Analysis of the results indicated that BMI and abdominal volume did not affect the accuracy of the step count obtained from accelerometers under any conditions. Walking speed, however, had a significant effect with step count accuracy decreasing at the slower speed.

An adaptive Kalman-based Bayes estimation technique to classify locomotor activities in young and elderly adults through accelerometers

An accelerometer-based system able to classify among different locomotor activities during real life conditions is here presented, and its performance evaluated. Epochs of walking at different speeds, and with different slopes, and stair descending and ascending, are detected, segmented, and classified by using an adaptation of a naïve 2D-Bayes classifier, which is updated on-line through the history of the estimated activities, in a Kalman-based scheme. The feature pair used for classification is mapped from an ensemble of 16 features extracted from the accelerometer data for each activity epoch. Two different versions of the classifier are presented to combine the multi-dimensional nature of the accelerometer data, and their results are compared in terms of correct recognition rate of the segmented activities, on two population samples of different age. The classification algorithm achieves correct classification rates higher than 90% and higher than 92%, for young and elderly adults, respectively.

Measurement of jerk-cost using a triaxial piezoelectric accelerometer for the evaluation of jaw movement smoothness

Jerk-cost as a measure of jaw movement smoothness has been used to evaluate the masticatory function of patients with tooth loss and malocclusion. Jerk-cost measuring systems have thus far been unable to determine the jerk-cost of each chewing phase over time. The purposes of this study were (i) to develop a new method for measuring momentary jerk-cost of the jaw movement using a small triaxial piezoelectric accelerometer and (ii) to test the hypothesis that the lowest smoothness is seen during jaw-opening phase. The accelerometer was attached to the skin of the mentum of each subject. Vertical jaw displacement, acceleration, the jerk, and the time differential of jerk-cost during gum chewing were analysed as a function of time in five normal dentate subjects (n = 5). The system revealed intra-class correlation coefficients of intra-examiner, inter-examiner, and test-retest consistency of substantially high values (0.80-0.88). In all subjects, the highest jerk-cost was observed in the opening phase of each chewing cycle when the gum was parting from the teeth; the lowest jerk-cost was observed in the intercuspal phase throughout the chewing cycle, thus confirming the hypothesis. Significant differences were observed between the opening, closing, and intercuspal chewing phases (N = 5, P = 0.007). The smoothness measurement system used in this study evaluated the momentary smoothness of each chewing phase in the masticatory cycle. The system may serve as a diagnostic tool to evaluate the smoothness of the jaw movement in general dental practice.

Accelerometry to Estimate Energy Expenditure during Activity: Best Practice with Data Loggers

Measurement of acceleration can be a proxy for energy expenditure during movement. The variable overall dynamic body acceleration (ODBA), used in recent studies, combines the dynamic elements of acceleration recorded in all three dimensions to measure acceleration and hence energy expenditure due to body movement. However, the simplicity of ODBA affords it limitations. Furthermore, while accelerometry data loggers enable measures to be stored, recording at high frequencies represents a limit to deployment periods as a result of logger memory and/or battery exhaustion. Using bantam chickens walking at different speeds in a respirometer while wearing an accelerometer logger, we investigated the best proxies for rate of oxygen consumption (Vo(2)) from a range of different models using acceleration. We also investigated the effects of sampling acceleration at different frequencies. The best predictor of Vo(2) was a multiple regression including individual measures of dynamic acceleration in each of the three dimensions. However, R(2) was relatively high for ODBA as well and also for certain measures of dynamic acceleration in single dimensions. The aforementioned are single variables, therefore easily derived onboard a data logger and from which a simple calibration equation can be derived. For calibrations of Vo(2) against ODBA, R(2) was consistent as sampling number decreased down to 600 samples of each acceleration channel per ODBA data point, beyond which R(2) tended to be considerably lower. In conclusion, data storage can be maximized when using acceleration as a proxy for Vo(2) by consideration of reductions in (1) number of axes measured and (2) sampling frequency.

A physical demands analysis of the 24-week British Army Parachute Regiment recruit training syllabus

This study assessed the physical demands of the 24-week Combined Infantryman's Course (CIC) for Parachute Regiment (Para) recruits and developed physical selection standards for applicants. Fifty recruits were monitored over five separate periods (35 d in total during weeks 1-2, 5, 9, 15 and 19-20). Energy expenditure (doubly labelled water), physical activity (accelerometry) and cardiovascular strain (% heart rate reserve) were measured. There was no overall progression in both the levels of physiological stress (physical activity counts and energy expenditure) and resultant cardiovascular strain during the first nine weeks of training. Applicants' 2.4 km run time and static lift strength measured at selection predicted 10 mile loaded march performance at the end of CIC Para. The introduction of job-related selection procedures and a more progressive approach to training has reduced the incidence of medical discharge from 14.4% to 5.1% and increased overall pass rates from 43% to 58%.