The application of human factors engineering for rehabilitation robots is based on a "human-centered" design philosophy that strives to provide safe and efficient human-robot interaction training for patients rather than depending on rehabilitation therapists. Human factors engineering for rehabilitation robots is undergoing preliminary investigation. However, the depth and breadth of current research do not provide a complete human factor engineering solution for developing rehabilitation robots. This study aims to provide a systematic review of research at the intersection of rehabilitation robotics and ergonomics to understand the progress and state-of-the-art research on critical human factors, issues, and corresponding solutions for rehabilitation robots. A total of 496 relevant studies were obtained from six scientific database searches, reference searches, and citation-tracking strategies. After applying the selection criteria and reading the full text of each study, 21 studies were selected for review and classified into four categories based on their human factor objectives: implementation of high safety, implementation of lightweight and high comfort, implementation of high human-robot interaction, and performance evaluation index and system studies. Based on the results of the studies, recommendations for future research are presented and discussed.
Delayed fluorescence (DF) is a unique emitting phenomenon of great interest for important applications in organic optoelectronics. In general, DF requires well-separated frontier orbitals, inherently corresponding to charge transfer (CT)-type emitters. However, facilitating intrinsic DF for local excited (LE)-type conjugated emitters remains very challenging. Aiming to overcome this obstacle, we demonstrate a new molecular design strategy with a DF-inactive B,N-multiple resonance (MR) emitter as a model system. Without the necessity of doping with heavy atoms, we synthesized a co-facial dimer in which an excimer-like state (S
Förster resonance energy transfer (FRET) has been widely applied in fluorescence imaging, sensing and so on, while developing useful strategy of boosting FRET efficiency becomes a key issue that limits the application. Except optimizing spectral properties, promoting orientation factor (κ
The deep-sea drilling rigs usually work in a complex waters and magnetic field environment and their attitude detection systems generally use a gyroscope to determine the output of the yaw angle. Deepwater rigs in seawater attitude detection and analysis of the characteristics of the MEMS gyroscope random drift come to a result that reducing the MEMS gyroscope random drift error is an important method to improve the precision of gyroscope and and it establishes a MEMS gyroscope random drift error model for MEMS gyroscope initial measurement data pre-processing and gives the random drift fitting valuation and compensation method to improve the accuracy of the gyroscope within a certain time.With OpenGL 3D controlling corrected detection, we can clearly see the effectiveness of the method after calibration.
Background: COVID-19 is an unprecedented public health emergency of international concern and has caused people to live in constant fear and posed a significant threat to their physical and mental health. Method: The study constructed a moderated mediation model to examine the mediating role of emotion regulation between collectivism and mental health and the moderating role of ego identity in the context of COVID-19. A total of 459 participants were recruited to complete the survey from 30 January to 8 May 2021.The Mental Health in COVID-19 Period Scale, Collectivism Tendency Scale, ERQ, and Identity Status Scale were used for the study. Results: (1) Expressive suppression played a mediating role in the relationship between collectivism and mental health; (2) The direct effect of collectivism on mental health and the path from expressive suppression to mental health were moderated by ego identity. Conclusion: The effect of collectivism on mental health is indirectly generated through expressive suppression and ego identity showing different patterns of regulation of mental health in different pathways, and its mechanisms and other important influences could be further explored in the future.
The small capacitor drivers use film capacitors instead of electrolytic capacitors in the DC-link, which will im- prove the life and reliability of the drivers. However, the DC-link voltage of the small capacitor drivers fluctuates seriously, and the AC component in it causes |(ω+6kωg)/ω|-th and |(ω−6kωg)/ω|-th harmonics in the extended back electromotive force (BEMF). These harmonics will increase the estimated position error in the sensorless driver. A harmonic suppression method based on adaptive synchronous rotating frame transformation (ASRFT) is presented in this article to improve the control accuracy of sensorless drivers with small capacitors. Firstly, the motor current harmonics caused by harmonics in the DC-link voltage are analyzed, and the relationship between these harmonics and the estimated sensorless position error was derived. Secondly, ASRFT and fixed synchronous rotation frame transformations (FSRFT) can be used to extract current harmonics in correspon- ding harmonic coordinate systems. Then the voltage compensation component generated by the harmonic compensation link will be injected into the driver to suppress the current harmonics extracted in the corresponding coordinate system. Finally, the controller parameters of the proposed method are designed. Using a 2kW PMSM Sensorless driver with a small capacitor, the proposed method is demonstrated to be effective.
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