Prolong walking is a notable risk factor for work-related lower-limb disorders (WRLLD) in industries such as agriculture, construction, service profession, healthcare and retail works. It is one of the common causes of lower limb fatigue or muscular exhaustion leading to poor balance and fall. Exoskeleton technology is seen as a modern strategy to assist worker's in these professions to minimize or eliminate the risk of WRLLDs. Exoskeleton has potentials to benefit workers in prolong walking (amongst others) by augmenting their strength, increasing their endurance, and minimizing high muscular activation, resulting in overall work efficiency and productivity. Controlling exoskeleton to achieve this purpose for able-bodied personnel without impeding their natural movement is, however, challenging. In this study, we propose a control strategy that integrates a Dual Unscented Kalman Filter (DUKF) for trajectory generation/prediction of the spatio-temporal features of human walking (i.e. joint position, and velocity, and acceleration) and an impedance cum supervisory controller to enable the exoskeleton to follow this trajectory to synchronize with the human walking. Experiment is conducted with four subjects carrying a load and walking at their normal speed- a typical scenario in industries. EMG signals taken at two muscles: Right Vastus Intermedius (on the thigh) and Right Gastrocnemius (on the calf) indicated reduction in muscular activation during the experiment. The results also show the ability of the control system to predict spatio-temporal features of the pilots' walking and to enable the exoskeleton to move in concert with the pilot.
In the current situation of global aging, the current market shortage of age-appropriate smart home products and the recent epidemic have led to greater isolation of the elderly, seriously affecting their physical and mental health. In order to optimize the sustainable user experience of the elderly when using smart home products, this paper proposes a research method based on Quality Function Deployment (QFD) for the optimal design of user experience of smart home products for the elderly, taking the design of age-appropriate home smart refrigerators as an example. Firstly, based on the results of market research and user interviews, the requirements of smart refrigerators for the elderly are screened and integrated, and the Kano model is used to prioritize these needs, resulting in the identification of important features needed in smart refrigerators for the elderly. Secondly, based on QFD, user requirements are transformed into design requirements, and a quality house model is established to ascertain the degree of importance of each design requirement through user ratings so as to obtain the key requirements as the theoretical basis for the solution design. Finally, optional solutions are generated for concept evaluation based on PUGH concept selection, comparing the advantages and disadvantages of the solutions and recombining them into an evaluation to determine the best solution. The quantitative evaluation of the four solutions reveals that Solution A has the highest score of 117.358, followed by Solution D with 113.259, Solution B with 96.415, and Solution C with 85.511, which is the lowest. The scoring allows the best design solution to be selected and applied to product development. The results show that the introduction of the Kano model and PUGH concept selection into QFD can be effectively used as a research method for optimizing the user experience of smart refrigerators for the elderly, and a corresponding design strategy for sustainable user experience optimization is proposed. The method and strategy provide guidance for the innovative design of new smart home products.