Development of a Wireless and Ambulatory Posture Monitoring System

The wireless and ambulatory posture monitoring system monitors the movement and posture change of the human body with respect to the g-line. It is crucial to monitor the posture health of the ophthalmologist who spends a prolonged period on the static sitting posture while operating on the slit lamp which leads to any painful experience. The motivation of the proposed system is to improve the ergonomics of the ophthalmologist on their working environment and reduce any occupational potential hazard which may prompt Work-Related Musculoskeletal Disorders (WMSDs). The proposed system also induced a wireless system by using XBee wireless units to reduce the use of the wire that may tangle on the study subject which causes any uncomfortable experience to the study subject during the human trial. Inertial Measurement Unit (IMU) sensor which consists of an Accelerometer, a Gyroscope and a Magnetometer is used to measure the angle of deviation of the body segment with respect to the g-line. The data is tabulated and presented into the graphical method to identify and extract the properties of the graph on each different static sitting posture which later are used for posture recognition

Computational Design of Wiring Layout on Tight Suits with Minimal Motion Resistance

An increasing number of electronics are directly embedded on the clothing to monitor human status (e.g., skeletal motion) or provide haptic feedback. A specific challenge to prototype and fabricate such a clothing is to design the wiring layout, while minimizing the intervention to human motion. We address this challenge by formulating the topological optimization problem on the clothing surface as a deformation-weighted Steiner tree problem on a 3D clothing mesh. Our method proposed an energy function for minimizing strain energy in the wiring area under different motions, regularized by its total length. We built the physical prototype to verify the effectiveness of our method and conducted user study with participants of both design experts and smart cloth users. On three types of commercial products of smart clothing, the optimized layout design reduced wire strain energy by an average of 77% among 248 actions compared to baseline design, and 18% over the expert design.Comment: This work is accepted at SIGGRAPH ASIA 2023(Conference Track

Posture Check – Creative Technological Approaches

“Posture Check: Creative Technological Approaches" explores new ways of giving individuals real-time visual feedback on changes in their posture to help them become more aware of their stance. This research follows to create various optical outputs transmitted by a sensor integrated with the wearable device that can regularly analyse an individual’s sitting posture and assist them in improving their sitting habits. The physical prototype is a posture awareness device that detects seating positions. When a person’s posture deteriorates, the device shares the data wirelessly to a nearby computer or phone and provides real-time feedback through digital visualisation prototypes, these visualisations present different methods of notifying people about their changing posture in an unobtrusive way. The prototype result is created through an iterative design and prototyping process, with a final version being examined for its influence on posture

Model-free Optimization of Trajectory And Impedance Parameters on Exercise Robots With Applications To Human Performance And Rehabilitation

This dissertation focuses on the study and optimization of human training and its physiological effects through the use of advanced exercise machines (AEMs). These machines provide an invaluable contribution to advanced training by combining exercise physiology with technology. Unlike conventional exercise machines (CEMs), AEMs provide controllable trajectories and impedances by using electric motors and control systems. Therefore, they can produce various patterns even in the absence of gravity. Moreover, the ability of the AEMs to target multiple physiological systems makes them the best available option to improve human performance and rehabilitation. During the early stage of the research, the physiological effects produced under training by the manual regulation of the trajectory and impedance parameters of the AEMs were studied. Human dynamics appear as not only complex but also unique and time-varying due to the particular features of each person such as its musculoskeletal distribution, level of fatigue,fitness condition, hydration, etc. However, the possibility of the optimization of the AEM training parameters by using physiological effects was likely, thus the optimization objective started to be formulated. Some previous research suggests that a model-based optimization of advanced training is complicated for real-time environments as a consequence of the high level of v complexity, computational cost, and especially the many unidentifiable parameters. Moreover, a model-based method differs from person to person and it would require periodic updates based on physical and psychological variations in the user. Consequently, we aimed to develop a model-free optimization framework based on the use of Extremum Seeking Control (ESC). ESC is a non-model based controller for real-time optimization which its main advantage over similar controllers is its ability to deal with unknown plants. This framework uses a physiological effect of training as bio-feedback. Three different frameworks were performed for single-variable and multi-variable optimization of trajectory and impedance parameters. Based on the framework, the objective is achieved by seeking the optimal trajectory and/or impedance parameters associated with the orientation of the ellipsoidal path to be tracked by the user and the stiffness property of the resistance by using weighted measures of muscle activations