Accelerometer-based prediction of skeletal mechanical loading during walking in normal weight to severely obese subjects

Estimation of Kinetics Using IMUs to Monitor and Aid in Clinical Decision-Making during ACL Rehabilitation: A Systematic Review

After an ACL injury, rehabilitation consists of multiple phases, and progress between these phases is guided by subjective visual assessments of activities such as running, hopping, jump landing, etc. Estimation of objective kinetic measures like knee joint moments and GRF during assessment can help physiotherapists gain insights on knee loading and tailor rehabilitation protocols. Conventional methods deployed to estimate kinetics require complex, expensive systems and are limited to laboratory settings. Alternatively, multiple algorithms have been proposed in the literature to estimate kinetics from kinematics measured using only IMUs. However, the knowledge about their accuracy and generalizability for patient populations is still limited. Therefore, this article aims to identify the available algorithms for the estimation of kinetic parameters using kinematics measured only from IMUs and to evaluate their applicability in ACL rehabilitation through a comprehensive systematic review. The papers identified through the search were categorized based on the modelling techniques and kinetic parameters of interest, and subsequently compared based on the accuracies achieved and applicability for ACL patients during rehabilitation. IMUs have exhibited potential in estimating kinetic parameters with good accuracy, particularly for sagittal movements in healthy cohorts. However, several shortcomings were identified and future directions for improvement have been proposed, including extension of proposed algorithms to accommodate multiplanar movements and validation of the proposed techniques in diverse patient populations and in particular the ACL population.

Raw Acceleration from Wrist- and Hip-Worn Accelerometers Corresponds with Mechanical Loading in Children and Adolescents

The purpose of this study was to investigate associations between peak magnitudes of raw acceleration (g) from wrist- and hip-worn accelerometers and ground reaction force (GRF) variables in a large sample of children and adolescents. A total of 269 participants (127 boys, 142 girls; age: 12.3 ± 2.0 yr) performed walking, running, jumping (<5 cm; >5 cm) and single-leg hopping on a force plate. A GENEActiv accelerometer was worn on the left wrist, and an Actigraph GT3X+ was worn on the right wrist and hip throughout. Mixed-effects linear regression was used to assess the relationships between peak magnitudes of raw acceleration and loading. Raw acceleration from both wrist and hip-worn accelerometers was strongly and significantly associated with loading (all p's < 0.05). Body mass and maturity status (pre/post-PHV) were also significantly associated with loading, whereas age, sex and height were not identified as significant predictors. The final models for the GENEActiv wrist, Actigraph wrist and Actigraph hip explained 81.1%, 81.9% and 79.9% of the variation in loading, respectively. This study demonstrates that wrist- and hip-worn accelerometers that output raw acceleration are appropriate for use to monitor the loading exerted on the skeleton and are able to detect short bursts of high-intensity activity that are pertinent to bone health.

Using Raw Accelerometer Data to Predict High-Impact Mechanical Loading

The purpose of this study was to develop peak ground reaction force (pGRF) and peak loading rate (pLR) prediction equations for high-impact activities in adult subjects with a broad range of body masses, from normal weight to severe obesity. A total of 78 participants (27 males; 82.4 ± 20.6 kg) completed a series of trials involving jumps of different types and heights on force plates while wearing accelerometers at the ankle, lower back, and hip. Regression equations were developed to predict pGRF and pLR from accelerometry data. Leave-one-out cross-validation was used to calculate prediction accuracy and Bland-Altman plots. Body mass was a predictor in all models, along with peak acceleration in the pGRF models and peak acceleration rate in the pLR models. The equations to predict pGRF had a coefficient of determination (R²) of at least 0.83, and a mean absolute percentage error (MAPE) below 14.5%, while the R² for the pLR prediction equations was at least 0.87 and the highest MAPE was 24.7%. Jumping pGRF can be accurately predicted through accelerometry data, enabling the continuous assessment of mechanical loading in clinical settings. The pLR prediction equations yielded a lower accuracy when compared to the pGRF equations.

Mechanical loading prediction through accelerometry data during walking and running

Currently, there is no way to assess mechanical loading variables such as peak ground reaction forces (pGRF) and peak loading rate (pLR) in clinical settings. The purpose of this study was to develop accelerometry-based equations to predict both pGRF and pLR during walking and running. One hundred and thirty one subjects (79 females; 76.9 ± 19.6kg) walked and ran at different speeds (2-14km·h^-1) on a force plate-instrumented treadmill while wearing accelerometers at their ankle, lower back and hip. Regression equations were developed to predict pGRF and pLR from accelerometry data. Leave-one-out cross-validation was used to calculate prediction accuracy and Bland-Altman plots. Our pGRF prediction equation was compared with a reference equation previously published. Body mass and peak acceleration were included for pGRF prediction and body mass and peak acceleration rate for pLR prediction. All pGRF equation coefficients of determination were above 0.96, and a good agreement between actual and predicted pGRF was observed, with a mean absolute percent error (MAPE) below 7.3%. Accuracy indices from our equations were better than previously developed equations. All pLR prediction equations presented a lower accuracy compared to those developed to predict pGRF. Walking and running pGRF can be predicted with high accuracy by accelerometry-based equations, representing an easy way to determine mechanical loading in free-living conditions. The pLR prediction equations yielded a somewhat lower prediction accuracy compared with the pGRF equations.

Accelerometer-based prediction of ground reaction force in head-out water exercise with different exercise intensity countermovement jump

Background

Water jumping exercise is an alternative method to achieve maintenance of bone health and reduce exercise injuries. Clarifying the ground reaction force (GRF) of moderate and high cardiopulmonary exercise intensities for jumping movements can help quantify the impact force during different exercise intensities. Accelerometers have been explored for measuring skeletal mechanical loading by estimating the GRFs. Predictive regression equations for GRF using ACC on land have already been developed and performed outside laboratory settings, whereas a predictive regression equation for GRF in water exercises is not yet established. The purpose of this study was to determine the best accelerometer wear-position for three exercise intensities and develop and validate the ground reaction force (GRF) prediction equation.

Methods

Twelve healthy women (23.6 ± 1.83 years, 158.2 ± 5.33 cm, 53.1 ± 7.50 kg) were recruited as participants. Triaxial accelerometers were affixed 3 cm above the medial malleolus of the tibia, fifth lumbar vertebra, and seventh cervical vertebra (C7). The countermovement jump (CMJ) cadence started at 80 beats/min and increased by 5 beats per 20 s to reach 50%, 65%, and 80% heart rate reserves, and then participants jumped five more times. One-way repeated analysis of variance was used to determine acceleration differences among wear-positions and exercise intensities. Pearson’s correlation was used to determine the correlation between the acceleration and GRF per body weight on land (GRF_VL_BW). Backward regression analysis was used to generate GRF_VL_BW prediction equations from full models with C7 acceleration (C7 ACC), age, percentage of water deep divided by body height (PWDH), and bodyweight as predictors. Paired t-test was used to determine GRF_VL_BW differences between values from the prediction equation and force plate measurement during validation. Lin’s CCC and Bland–Altman plots were used to determine the agreement between the predicted and force plate-measured GRF_VL_BW.

Results

The raw full profile data for the resultant acceleration showed that the acceleration curve of C7 was similar to that of GRFv. The predicted formula was − 1.712 + 0.658 * C7ACC + 0.016 * PWDH + 0.008 * age + 0.003*weight. Lin’s CCC score was 0.7453, with bias of 0.369%.

Conclusion

The resultant acceleration measured at C7 was identified as the valid estimated GRF_VL_BW during CMJ in water.

The effect of bariatric surgery on gravitational loading and its impact on bone mass

INTRODUCTION

Mechanical unloading associated with weight loss might be one of the main causes for bariatric surgery (BS) induced bone loss. However, no study has tested this hypothesis through objectively measured accelerometry-derived gravitational loading. We aimed to assess how gravitational loading changes following BS and how this correlates with bone mass losses.

METHODS

Twenty-one patients submitted to gastric bypass were assessed before, 1, 6 and 12 months after BS for areal bone mineral density (BMD), calciotropic hormones, sclerostin, body composition and daily physical activity. Gravitational loading was determined as the sum of ground reaction forces assessed by accelerometer which considered the interaction between weight and daily ambulation.

RESULTS

Mechanical stimuli promoted through the significant increase in steps number counterbalanced the gravitational loading decreases derived from the significant weight loss after BS. Gravitational loading volume decreased between pre-BS and 1 month post-BS (-2215 kN·d^-1; p = .023), but remained stable between 6 and 12 months post-BS, despite decreases on hip (-7.0%; p < .001), femoral neck (-8.8%; p < .001) and lumbar spine (-5.2%; p < .001) BMD. Serum sclerostin increased from pre-BS to 1 month post-BS (+0.118 ng·mL^-1; p = .021), returning to pre-BS levels 6 months after surgery. Neither vitamin D nor parathyroid hormone were affected by BS. Weight variation was a predictor of BMD decreases at total hip (R² = 0.06; p = .026) and femoral neck (R² = 0.12; p = .022), whereas daily gravitational loading volume was not. Fat and lean mass changes were also predictors of BMD decrease at total hip (R² = 0.05; p = .031) and femoral neck (R² = 0.14; p = .010), respectively.

CONCLUSION

Our findings suggest that gravitational loading only decreased during the first month after surgery remaining stable thereafter, and these changes do not seem to explain BS-induced bone loss. The association between weight and bone loss seems to result from other physiological aspects, fat and lean mass loss, rather than from gravitational loading decrease.

Wearable Devices for Physical Activity and Healthcare Monitoring in Elderly People: A Critical Review

The availability of wearable devices (WDs) to collect biometric information and their use during activities of daily living is significantly increasing in the general population. These small electronic devices, which record fitness and health-related outcomes, have been broadly utilized in industries such as medicine, healthcare, and fitness. Since they are simple to use and progressively cheaper, they have also been used for numerous research purposes. However, despite their increasing popularity, most of these WDs do not accurately measure the proclaimed outcomes. In fact, research is equivocal about whether they are valid and reliable methods to specifically evaluate physical activity and health-related outcomes in older adults, since they are mostly designed and produced considering younger subjects' physical and mental characteristics. Additionally, their constant evolution through continuous upgrades and redesigned versions, suggests the need for constant up-to-date reviews and research. Accordingly, this article aims to scrutinize the state-of-the-art scientific evidence about the usefulness of WDs, specifically on older adults, to monitor physical activity and health-related outcomes. This critical review not only aims to inform older consumers but also aid researchers in study design when selecting physical activity and healthcare monitoring devices for elderly people.

The Effect of an Exercise Intervention Program on Bone Health After Bariatric Surgery: A Randomized Controlled Trial

Exercise has been suggested as a therapeutic approach to attenuate bone loss induced by bariatric surgery (BS), but its effectiveness remains unclear. Our aim was to determine if an exercise-training program could induce benefits on bone mass after BS. Eighty-four patients, submitted to gastric bypass or sleeve gastrectomy, were randomized to either exercise (EG) or control group (CG). One month post-BS, EG underwent a 11-month supervised multicomponent exercise program, while CG received only standard medical care. Patients were assessed before BS and at 1, 6, and 12 months post-BS for body composition, areal bone mineral density (BMD), bone turnover markers, calciotropic hormones, sclerostin, bone material strength index, muscle strength, and daily physical activity. A primary analysis was conducted according to intention-to-treat principles and the primary outcome was the between-group difference on lumbar spine BMD at 12 months post-BS. A secondary analysis was also performed to analyze if the exercise effect depended on training attendance. Twelve months post-BS, primary analysis results revealed that EG had a higher BMD at lumbar spine (+0.024 g∙cm^-2 [95% confidence interval (CI) 0.004, 0.044]; p = .015) compared with CG. Among total hip, femoral neck, and 1/3 radius secondary outcomes, only 1/3 radius BMD improved in EG compared with CG (+0.013 g∙cm^-2 [95% CI 0.003, 0.023]; p = .020). No significant exercise effects were observed on bone biochemical markers or bone material strength index. EG also had a higher lean mass (+1.5 kg [95% CI 0.1, 2.9]; p = .037) and higher number of high impacts (+51.4 [95% CI 6.6, 96.1]; p = .026) compared with CG. In addition, secondary analysis results suggest that exercise-induced benefits may be obtained on femoral neck BMD but only on those participants with ≥50% exercise attendance compared with CG (+5.3% [95% CI 2.0, 8.6]; p = .006). Our findings suggest that an exercise program is an effective strategy to ameliorate bone health in post-BS patients. © 2020 American Society for Bone and Mineral Research (ASBMR).