Body Segment Kinematics and Energy Expenditure in Active Videogames

Prediction of energy expenditure during activities of daily living by a wearable set of inertial sensors

Physical inactivity is responsible for 7-10% of all premature deaths worldwide. Thus, valid, reliable and unobtrusive methods for monitoring activities of daily living (ADL) to predict total energy expenditure (TEE) is desired. Multiple methods exist to quantify TEE, but microelectromechanical systems (MEMSs) are the only method, which has shown promising results and are applicable for long-term monitoring in the field. However, no perfect method exists for predicting TEE on a daily basis. The present study evaluates TEE estimation based on a MEMS (Xsens Link system) taking gender and heart rate into account. Fifteen individuals performed seven ADL wearing the Xsens Link system, a heart rate belt and an oxygen mask. Multiple linear regression models were established for sedentary and dynamic activities and evaluated by leave-one-out cross-validation and compared with indirect calorimetry. The linear regression model showed better prediction for dynamic activities (adjusted R² 0.95±0.16) compared to sedentary activities (adjusted R² 0.61±0.19). The root-mean-square error for the TEE estimation ranged between 0.02 and 0.08 kJ/min/kg for the sedentary and dynamic models, respectively. The study showed a viable approach to predict TEE in ADL compared to previously published results. Further studies are warranted to reduce the number of sensors in the estimation of TEE.

Wrap-Around Wearable Coils for Seamless Monitoring of Joint Flexion

OBJECTIVE

We introduce and validate a new class of wearable coils that seamlessly monitor joint flexion in the individual's natural environment while overcoming shortcomings in state-of-the-art.

METHODS

Our approach relies on Faraday's law of induction and employs wrap-around transmit and receive coils that get angularly misaligned as the joint flexes.

RESULTS

Simulation and in vitro measurement results for both copper and e-thread coils are in excellent agreement. As a proof-of-concept, a cylindrical arm model is considered and feasibility of monitoring the 0°-130° range of motion is confirmed. The operation frequency of 34 MHz is identified as optimal, bringing forward reduced power requirements, enhanced angular resolution, and extreme robustness to tissue dielectric property variations. Performance benchmarking versus state-of-the-art inertial measurement units shows equivalent or superior performance, particularly for flexion angles greater than 20°. Design guidelines and safety considerations are also explored.

CONCLUSION

Contrary to "gold-standard" camera-based motion capture, the reported approach is not restricted to contrived environments. Concurrently, it does not suffer from integration drift (unlike inertial measurement units), it does not require line-of-sight (unlike time-of-flight sensors), and it does not restrict natural joint movement (unlike bending sensors).

SIGNIFICANCE

The reported approach is envisioned to be seamlessly integrated into garments and, eventually, redefine the way joint flexion is monitored at present. This promises unprecedented opportunities for rehabilitation, sports, gestural interaction, and more.

On the biomechanical analysis of the calories expended in a straight boxing jab

Boxing and related sports activities have become a standard workout regime at many fitness studios worldwide. Oftentimes, people are interested in the calories expended during these workouts. This note focuses on determining the calories in a boxer's jab, using kinematic vector-loop relations and basic work-energy principles. Numerical simulations are undertaken to illustrate the basic model. Multi-limb extensions of the model are also discussed.