Transactions on Human Machine Systems - IEEE SMC

This article proposes a novel evaluation approach on wearing passive upper-limb exoskeletons for overhead tasks in real-world automotive manufacturing lines. We determined that wearing exoskeletons reduced the biomechanical efforts of workers measured by joint kinematics and electromyography as well as the estimated shoulder joint reaction forces and torques derived from...

Neural or muscular injuries, such as due to amputation, spinal cord injury, and stroke, can affect hand functions, profoundly impacting independent living. This has motivated the advancement of cutting-edge assistive robotic hands. However, unintuitive myoelectric control of these devices remains challenging, which limits the clinical translation of these devices. Accordingly,...

This article introduces the global-local image perceptual score (GLIPS), an image metric designed to assess the photorealistic image quality of AI-generated images with a high degree of alignment to human visual perception. Traditional metrics such as Fréchet inception distance (FID) and kernel inception distance scores do not align closely with...

Lower-limb active exoskeletons may experience errors in operational settings due to imperfect algorithms, which may impact users' trust in the system and the human-exoskeleton fluency (the coordination of actions between the human and exoskeleton). In this study, we introduced pseudorandom catch trials (errors) in 1.68% of all strides, where an...

Predicting workers' body postures is crucial for effective ergonomic interventions to reduce musculoskeletal disorders (MSDs). In this study, we employ a novel generative approach to predict human postures during manual material handling tasks. Specifically, we implement two distinct network architectures, U-Net and multilayer perceptron (MLP), to build the diffusion model....