Raymond C. Browning

Monitoring of Posture Allocations and Activities by a Shoe-Based Wearable Sensor

Monitoring of posture allocations and activities enables accurate estimation of energy expenditure and may aid in obesity prevention and treatment. At present, accurate devices rely on multiple sensors distributed on the body and thus may be too obtrusive for everyday use. This paper presents a novel wearable sensor, which is capable of very accurate recognition of common postures and activities. The patterns of heel acceleration and plantar pressure uniquely characterize postures and typical activities while requiring minimal preprocessing and no feature extraction. The shoe sensor was tested in nine adults performing sitting and standing postures and while walking, running, stair ascent/descent and cycling. Support vector machines (SVMs) were used for classification. A fourfold validation of a six-class subject-independent group model showed 95.2% average accuracy of posture/activity classification on full sensor set and over 98% on optimized sensor set. Using a combination of acceleration/pressure also enabled a pronounced reduction of the sampling frequency (25 to 1 Hz) with out significant loss of accuracy (98% versus 93%). Subjects had shoe sizes (US) M9.5-11 and W7-9 and body mass index from 18.1 to 39.4 kg/m2 and thus suggesting that the device can be used by individuals with varying anthropometric characteristics.

Exploiting social networks to mitigate the obesity epidemic.

Despite significant efforts, obesity continues to be a major public health problem, and there are surprisingly few effective strategies for its prevention and treatment. We now realize that healthy diet and activity patterns are difficult to maintain in the current physical environment. Recently, it was suggested that the social environment also contributes to obesity. Therefore, using network‐based interaction models, we simulate how obesity spreads along social networks and predict the effectiveness of large‐scale weight management interventions. For a wide variety of conditions and networks, we show that individuals with similar BMIs will cluster together into groups, and if left unchecked, current social forces will drive these groups toward increasing obesity. Our simulations show that many traditional weight management interventions fail because they target overweight and obese individuals without consideration of their surrounding cluster and wider social network. The popular strategy for dieting with friends is shown to be an ineffective long‐term weight loss strategy, whereas dieting with friends of friends can be somewhat more effective by forcing a shift in cluster boundaries. Fortunately, our simulations also show that interventions targeting well‐connected and/or normal weight individuals at the edges of a cluster may quickly halt the spread of obesity. Furthermore, by changing social forces and altering the behavior of a small but random assortment of both obese and normal weight individuals, highly effective network‐driven strategies can reverse current trends and return large segments of the population to a healthier weight.

A comparison of energy expenditure estimation of several physical activity monitors.

INTRODUCTION Accurately and precisely estimating free-living energy expenditure (EE) is important for monitoring energy balance and quantifying physical activity. Recently, single and multisensor devices have been developed that can classify physical activities, potentially resulting in improved estimates of EE. PURPOSE This study aimed to determine the validity of EE estimation of a footwear-based physical activity monitor and to compare this validity against a variety of research and consumer physical activity monitors. METHODS Nineteen healthy young adults (10 men, 9 women) completed a 4-h stay in a room calorimeter. Participants wore a footwear-based physical activity monitor as well as Actical, ActiGraph, IDEEA, DirectLife, and Fitbit devices. Each individual performed a series of postures/activities. We developed models to estimate EE from the footwear-based device, and we used the manufacturers software to estimate EE for all other devices. RESULTS Estimated EE using the shoe-based device was not significantly different than measured EE (mean ± SE; 476 ± 20 vs 478 ± 18 kcal, respectively) and had a root-mean-square error of 29.6 kcal (6.2%). The IDEEA and the DirectLlife estimates of EE were not significantly different than the measured EE, but the ActiGraph and the Fitbit devices significantly underestimated EE. Root-mean-square errors were 93.5 (19%), 62.1 kcal (14%), 88.2 kcal (18%), 136.6 kcal (27%), 130.1 kcal (26%), and 143.2 kcal (28%) for Actical, DirectLife, IDEEA, ActiGraph, and Fitbit, respectively. CONCLUSIONS The shoe-based physical activity monitor provides a valid estimate of EE, whereas the other physical activity monitors tested have a wide range of validity when estimating EE. Our results also demonstrate that estimating EE based on classification of physical activities can be more accurate and precise than estimating EE based on total physical activity.

Obesity does not increase external mechanical work per kilogram body mass during walking

Walking is the most common type of physical activity prescribed for the treatment of obesity. The net metabolic rate during level walking (W/kg) is approximately 10% greater in obese vs. normal weight adults. External mechanical work (W(ext)) is one of the primary determinants of the metabolic cost of walking, but the effects of obesity on W(ext) have not been clearly established. The purpose of this study was to compare W(ext) between obese and normal weight adults across a range of walking speeds. We hypothesized that W(ext) (J/step) would be greater in obese adults but W(ext) normalized to body mass would be similar in obese and normal weight adults. We collected right leg three-dimensional ground reaction forces (GRF) while twenty adults (10 obese, BMI=35.6 kg/m(2) and 10 normal weight, BMI=22.1 kg/m(2)) walked on a level, dual-belt force measuring treadmill at six speeds (0.50-1.75 m/s). We used the individual limb method (ILM) to calculate external work done on the center of mass. Absolute W(ext) (J/step) was greater in obese vs. normal weight adults at each walking speed, but relative W(ext) (J/step/kg) was similar between the groups. Step frequencies were not different. These results suggest that W(ext) is not responsible for the greater metabolic cost of walking (W/kg) in moderately obese adults.

Effects of Obesity on Lower Extremity Muscle Function During Walking at Two Speeds

Walking is a recommended form of physical activity for obese adults, yet the effects of obesity and walking speed on the biomechanics of walking are not well understood. The purpose of this study was to examine joint kinematics, muscle force requirements and individual muscle contributions to the walking ground reaction forces (GRFs) at two speeds (1.25 ms(-1) and 1.50 ms(-1)) in obese and nonobese adults. Vasti (VAS), gluteus medius (GMED), gastrocnemius (GAST), and soleus (SOL) forces and their contributions to the GRFs were estimated using three-dimensional musculoskeletal models scaled to the anthropometrics of nine obese (35.0 (3.78 kg m(-2))); body mass index mean (SD)) and 10 nonobese (22.1 (1.02 kg m(-2))) subjects. The obese individuals walked with a straighter knee in early stance at the faster speed and greater pelvic obliquity during single limb support at both speeds. Absolute force requirements were generally greater in obese vs. nonobese adults, the main exception being VAS, which was similar between groups. At both speeds, lean mass (LM) normalized force output for GMED was greater in the obese group. Obese individuals appear to adopt a gait pattern that reduces VAS force output, especially at speeds greater than their preferred walking velocity. Greater relative GMED force requirements in obese individuals may contribute to altered kinematics and increased risk of musculoskeletal injury/pathology. Our results suggest that obese individuals may have relative weakness of the VAS and hip abductor muscles, specifically GMED, which may act to increase their risk of musculoskeletal injury/pathology during walking, and therefore may benefit from targeted muscle strengthening.

Childhood obesity and walking: guidelines and challenges.

The development and maintenance of excess body mass in many children is partly attributable to levels of physical activity that are lower than the recommended 60 minutes/day. Walking is a recommended form of physical activity for obese children, due to its convenience and perceived ease of adoption. Unfortunately, studies that have used objective physical activity assessment continue to report low step counts and levels of physical activity in obese children. This may be due to physiological and/or biomechanical factors that make walking more difficult for obese children. The purpose of this review is to highlight the current recommended and measured levels of physical activity for children and to discuss the physiological and biomechanical challenges of walking for obese children that may help explain why these children are not meeting physical activity goals.

Accurate prediction of energy expenditure using a shoe-based activity monitor.

PURPOSE The aim of this study was to develop and validate a method for predicting energy expenditure (EE) using a footwear-based system with integrated accelerometer and pressure sensors. METHODS We developed a footwear-based device with an embedded accelerometer and insole pressure sensors for the prediction of EE. The data from the device can be used to perform accurate recognition of major postures and activities and to estimate EE using the acceleration, pressure, and posture/activity classification information in a branched algorithm without the need for individual calibration. We measured EE via indirect calorimetry as 16 adults (body mass index=19-39 kg·m) performed various low- to moderate-intensity activities and compared measured versus predicted EE using several models based on the acceleration and pressure signals. RESULTS Inclusion of pressure data resulted in better accuracy of EE prediction during static postures such as sitting and standing. The activity-based branched model that included predictors from accelerometer and pressure sensors (BACC-PS) achieved the lowest error (e.g., root mean squared error (RMSE)=0.69 METs) compared with the accelerometer-only-based branched model BACC (RMSE=0.77 METs) and nonbranched model (RMSE=0.94-0.99 METs). Comparison of EE prediction models using data from both legs versus models using data from a single leg indicates that only one shoe needs to be equipped with sensors. CONCLUSIONS These results suggest that foot acceleration combined with insole pressure measurement, when used in an activity-specific branched model, can accurately estimate the EE associated with common daily postures and activities. The accuracy and unobtrusiveness of a footwear-based device may make it an effective physical activity monitoring tool.

How tibiofemoral alignment and contact locations affect predictions of medial and lateral tibiofemoral contact forces

Understanding degeneration of biological and prosthetic knee joints requires knowledge of the in-vivo loading environment during activities of daily living. Musculoskeletal models can estimate medial/lateral tibiofemoral compartment contact forces, yet anthropometric differences between individuals make accurate predictions challenging. We developed a full-body OpenSim musculoskeletal model with a knee joint that incorporates subject-specific tibiofemoral alignment (i.e. knee varus-valgus) and geometry (i.e. contact locations). We tested the accuracy of our model and determined the importance of these subject-specific parameters by comparing estimated to measured medial and lateral contact forces during walking in an individual with an instrumented knee replacement and post-operative genu valgum (6°). The errors in the predictions of the first peak medial and lateral contact force were 12.4% and 11.9%, respectively, for a model with subject-specific tibiofemoral alignment and contact locations determined through radiographic analysis, vs. 63.1% and 42.0%, respectively, for a model with generic parameters. We found that each degree of tibiofemoral alignment deviation altered the first peak medial compartment contact force by 51N (r(2)=0.99), while each millimeter of medial-lateral translation of the compartment contact point locations altered the first peak medial compartment contact force by 41N (r(2)=0.99). The model, available at www.simtk.org/home/med-lat-knee/, enables the specification of subject-specific joint alignment and compartment contact locations to more accurately estimate medial and lateral tibiofemoral contact forces in individuals with non-neutral alignment.

Energetics and Biomechanics of Inclined Treadmill Walking in Obese Adults

UNLABELLED Brisk walking is a recommended form of exercise for obese individuals. However, lower-extremity joint loads and the associated risk of musculoskeletal injury or pathological disease increase with walking speed. Walking uphill at a slower speed is an alternative form of moderate intensity exercise that may reduce joint loading. PURPOSE The purpose of this study was to quantify the energetics and biomechanics of level and uphill walking in obese adults. We hypothesized that compared to brisk level walking, walking slower up a moderate incline would reduce lower-extremity net muscle moments while providing appropriate cardiovascular stimulus. METHODS Twelve obese adult volunteers, with mass of 100.5±15.7 kg and body mass index of 33.4±2.6 kg·m (mean±SD), participated in this study. We measured oxygen consumption, ground reaction forces, and three-dimensional lower-extremity kinematics while subjects walked on a dual-belt force-measuring treadmill at several speed (0.50-1.75 m·s) and grade (0°-9°) combinations. We calculated metabolic rate, loading rates, and net muscle moments at the hip, knee, and ankle for each condition. RESULTS Metabolic rates were similar across trials and were of moderate intensity (48.5%-59.8% of VO2max). Walking slower uphill significantly reduced loading rates and lower-extremity net muscle moments compared with faster level walking. Peak knee extension and adduction moments were reduced by ∼19% and 26%, respectively, when subjects walked up a 6° incline at 0.75 m·s versus level walking at 1.50 m·s. CONCLUSIONS These results suggest that walking at a relatively slow speed up a moderate incline is a potential exercise strategy that may reduce the risk of musculoskeletal injury/pathological disease while providing proper cardiovascular stimulus in obese adults.

A Comparison of Slow, Uphill and Fast, Level Walking on Lower Extremity Biomechanics and Tibiofemoral Joint Loading in Obese and Nonobese Adults

We determined if slow, uphill walking (0.75 m/s, 6°) reduced tibiofemoral (TF) loading compared to faster, level walking (1.50 m/s) in obese and nonobese adults. We collected kinematic, kinetic, and electromyographic data as 9 moderately obese and 10 nonobese participants walked on a dual‐belt instrumented treadmill. We used OpenSim to scale a musculoskeletal model and calculate joint kinematics, kinetics, muscle forces, and TF forces. Compressive TF forces were greater in the obese adults during both speed/grade combinations. During level walking, obese participants walked with a straighter leg than nonobese participants, resulting in early stance vasti muscle forces that were similar in the obese and nonobese participants. Early stance peak compressive TF forces were reduced by 23% in obese (2,352 to 1,811 N) and 35% in nonobese (1,994 to 1,303 N) individuals during slow, uphill walking compared to brisk level walking. Late stance peak TF forces were similar across speeds/grades, but were greater in obese (∼2,900 N) compared to nonobese (∼1,700 N) individuals. Smaller early stance TF loads and loading rates suggest that slow, uphill walking may be appropriate exercise for obese individuals at risk for musculoskeletal pathology or pain.