The loadsol^® wireless in-shoe force sensors can be useful for in-field measurements. However, its accuracy is unknown in the military context, whereby soldiers have to carry heavy loads and walk in military boots. The purpose of this study was to establish the validity of the loadsol^® sensors in military personnel during loaded walking on flat, inclined and declined surfaces. Full-time Singapore Armed Forces (SAF) personnel (n = 8) walked on an instrumented treadmill on flat, 10° inclined, and 10° declined gradients while carrying heavy loads (25 kg and 35 kg). Normal ground reaction forces (GRF), perpendicular to the contact surface, were simultaneously measured using both the loadsol^® sensors inserted in the military boots and the Bertec instrumented treadmill as the gold standard. A total of eight variables of interest were compared between loadsol^® and treadmill, including four kinetic (impact peak force, active peak force, impulse, loading rate) and four spatiotemporal (stance time, stride time, cadence, step length) variables. Validity was assessed using Bland–Altman plots and 95% Limits of Agreement (LoA). Bias was calculated as the mean difference between the values obtained from loadsol^® and the instrumented treadmill. Results showed similar force-time profiles between loadsol^® sensors and the instrumented treadmill. The bias of most variables was generally low, with a narrow range of LoA. The high accuracy and good agreement with standard laboratory equipment suggest that the loadsol^® system is a valid tool for measuring normal GRF during walking in military boots under heavy load carriage.

Military operators performing vehicle maintenance work are at times subject to onerous tasks such as lifting and transporting heavy loads, potentially in confined spaces. As this presents a risk for developing musculoskeletal injury, it is of interest to evaluate if a passive back-support exosuit could help reduce back muscle load. This study used wireless electromyographic (EMG) sensors to evaluate the biomechanical effects of exosuits during lifting tasks. Ten male participants performed military-relevant lifting tasks with and without wearing the exosuit in randomised orders. The lifting tasks included (1) vertical lifts of different weights (15 and 25 kg) onto different platform heights (0.5 m and 1.2 m) and (2) a lateral walk task across 4 m in a confined space while carrying a 39 kg weight. EMG activities of three back muscle groups (longissimus, iliocostalis, and multifidus) were measured and normalised to maximal isometric back extension tasks. The results showed no significant differences in muscle activation between conditions in most lifting tasks, except for a reduction in longissimus muscle activity when using the exosuit during lateral walking. Individual responses varied substantially, with some participants showing reduced muscle activity, while others did not. These findings highlight the challenges in implementing exosuits in reducing back muscle load during military lifting tasks. While passive back-support exosuits may provide benefits to some users, their effectiveness varies among individuals and may be task-dependent.

Quantitative gait analysis is important for assessing and rehabilitating lower-limb prosthetic users, but markerless motion capture has been challenging for this population due to the difficulty in detecting prosthetic joints using models trained primarily on able-bodied individuals. This study proposes a zero-shot method leveraging generative diffusion models to transform prosthetic limb images into able-bodied representations that standard pose estimation models can detect, eliminating the need for additional data collection or model retraining. Videos of unilateral transfemoral and transtibial amputees walking were obtained publicly from YouTube. For each video frame, an edge map was generated and used as input to a ControlNet diffusion model, generating a synthetic image resembling an able-bodied person while preserving the person’s original pose. These synthetic images were then passed through OpenPose. The zero-shot approach achieved substantial reductions in keypoint coordinate errors of 37% for transtibial and 76% for transfemoral prosthetic limbs compared to OpenPose on the original videos. The method enabled the identification and quantification of key gait deviations such as reduced knee flexion and altered kinematics timing between prosthetic and intact limbs. While the results demonstrate the feasibility of markerless gait analysis for lower-limb prosthetic users, the study’s findings are based on a limited dataset of publicly available videos, and caution should be exercised in generalizing the results to broader populations due to the varying nature of prosthetic designs. Nonetheless, this approach has the potential to facilitate personalized rehabilitation using standard consumer cameras and existing pose estimation models.