A brain-computer interface(BCI)-based electric wheelchair control system was developed, which enables the users to move the wheelchair forward or backward, and turn left or right without any pre-learning. This control...A brain-computer interface(BCI)-based electric wheelchair control system was developed, which enables the users to move the wheelchair forward or backward, and turn left or right without any pre-learning. This control system makes use of the amplitude enhancement of alpha-wave blocking in electroencephalogram(EEG) when eyes close for more than 1 s to constitute a BCI for the switch control of wheelchair movements. The system was formed by BCI control panel, data acquisition, signal processing unit and interface control circuit. Eight volunteers participated in the wheelchair control experiments according to the preset routes. The experimental results show that the mean success control rate of all the subjects was 81.3%, with the highest reaching 93.7%. When one subject's triggering time was 2.8 s, i.e., the flashing time of each cycle light was 2.8 s, the average information transfer rate was 8.10 bit/min, with the highest reaching 12.54 bit/min.展开更多
Background: The functionality and the safety of the electric wheelchairs were essential for users’ everyday life. Some evidence indicated that the wheelchair Per Se highly influenced users’ occupational life, their ...Background: The functionality and the safety of the electric wheelchairs were essential for users’ everyday life. Some evidence indicated that the wheelchair Per Se highly influenced users’ occupational life, their personal identity and social life;further, the wheelchair became an extension of the body and more than a technical device. Besides, there was still both environmental and self-efficacy or/and mental health factors obstacles for full social participation. Even so, there was to some extent stigma related to being a wheelchair user. There was a need to reflect users’ perspective on being depended on electric wheelchair. The aim, accordingly, was to describe and to get a deeper insight into electric wheelchairs users’ perspective and experiences of utilizing this device;a qualitative design with an inductive approach was used. Method: Qualitative latent and interpretative content analysis [1] [2] was used after repeated face-to-face semi-structured interviews with three experienced Swedish electric wheelchair users during the autumn 2017. Findings: The findings showed a high degree of dependability of the assistants that supported the users, and of the quality of that working relationship. The findings were formulated, abstracted and interpreted in several steps. It showed one theme of meaning: “Living in a space shifting between potential violation of or respect for human dignity”. Conclusion: The study showed that electric wheelchair users were relatively content with their lives as well as with their devices in turns of mobility and accessibility, but the meaning of their narrations showed a life at constant risk of having the respect of human rights and human respect violated. Besides, the importance of having access to good and high quality devices, good staffing, and environmental support, all in concordance with human rights, the clinical and practical implications of this study narrows down to a question of encountering the other person as a whole and worthy individual.展开更多
In order to achieve a wheelchair climb stairs function, this paper designs a star-wheel stair-climbing mechanism. Through the effect of the lock coupling, the star-wheel stair-climbing mechanism is formed to be fixed ...In order to achieve a wheelchair climb stairs function, this paper designs a star-wheel stair-climbing mechanism. Through the effect of the lock coupling, the star-wheel stair-climbing mechanism is formed to be fixed axis gear train or planetary gear train achieving flat-walking and stair-climbing functions. Crossing obstacle analysis obtains the maximum height and minimum width of obstacle which the wheelchair can cross. Stress-strain analysis in Solidworks simulation is performed to verify material strength.展开更多
This paper represented Autoregressive Neural Network (ARNN) and meant threshold methods for recognizing eye movements for control of an electrical wheelchair using EEG technology. The eye movements such as eyes open, ...This paper represented Autoregressive Neural Network (ARNN) and meant threshold methods for recognizing eye movements for control of an electrical wheelchair using EEG technology. The eye movements such as eyes open, eyes blinks, glancing left and glancing right related to a few areas of human brain were investigated. A Hamming low pass filter was applied to remove noise and artifacts of the eye signals and to extract the frequency range of the measured signals. An autoregressive model was employed to produce coefficients containing features of the EEG eye signals. The coefficients obtained were inserted the input layer of a neural network model to classify the eye activities. In addition, a mean threshold algorithm was employed for classifying eye movements. Two methods were compared to find the better one for applying in the wheelchair control to follow users to reach the desired direction. Experimental results of controlling the wheelchair in the indoor environment illustrated the effectiveness of the proposed approaches.展开更多
基金Supported by the National Natural Science Foundation of China(No.81222021,No.30970875,No.90920015,No.61172008 and No.81171423)National Key Technology Research and Development Program of the Ministry of Science and Technology of China(No.2012BAI34B02)Program for New Century Excellent Talents in University of the Ministry of Education of China(No.NCET-10-0618)
文摘A brain-computer interface(BCI)-based electric wheelchair control system was developed, which enables the users to move the wheelchair forward or backward, and turn left or right without any pre-learning. This control system makes use of the amplitude enhancement of alpha-wave blocking in electroencephalogram(EEG) when eyes close for more than 1 s to constitute a BCI for the switch control of wheelchair movements. The system was formed by BCI control panel, data acquisition, signal processing unit and interface control circuit. Eight volunteers participated in the wheelchair control experiments according to the preset routes. The experimental results show that the mean success control rate of all the subjects was 81.3%, with the highest reaching 93.7%. When one subject's triggering time was 2.8 s, i.e., the flashing time of each cycle light was 2.8 s, the average information transfer rate was 8.10 bit/min, with the highest reaching 12.54 bit/min.
文摘Background: The functionality and the safety of the electric wheelchairs were essential for users’ everyday life. Some evidence indicated that the wheelchair Per Se highly influenced users’ occupational life, their personal identity and social life;further, the wheelchair became an extension of the body and more than a technical device. Besides, there was still both environmental and self-efficacy or/and mental health factors obstacles for full social participation. Even so, there was to some extent stigma related to being a wheelchair user. There was a need to reflect users’ perspective on being depended on electric wheelchair. The aim, accordingly, was to describe and to get a deeper insight into electric wheelchairs users’ perspective and experiences of utilizing this device;a qualitative design with an inductive approach was used. Method: Qualitative latent and interpretative content analysis [1] [2] was used after repeated face-to-face semi-structured interviews with three experienced Swedish electric wheelchair users during the autumn 2017. Findings: The findings showed a high degree of dependability of the assistants that supported the users, and of the quality of that working relationship. The findings were formulated, abstracted and interpreted in several steps. It showed one theme of meaning: “Living in a space shifting between potential violation of or respect for human dignity”. Conclusion: The study showed that electric wheelchair users were relatively content with their lives as well as with their devices in turns of mobility and accessibility, but the meaning of their narrations showed a life at constant risk of having the respect of human rights and human respect violated. Besides, the importance of having access to good and high quality devices, good staffing, and environmental support, all in concordance with human rights, the clinical and practical implications of this study narrows down to a question of encountering the other person as a whole and worthy individual.
基金Supported Special Topic of the Ministry of Education about Humanities and Social Sciences of China(12JDGC007)University Natural Science Research Projects of Anhui Province(KJ2011ZD01)Science and Technology Research Project of Anhui Province(1301022052)
文摘In order to achieve a wheelchair climb stairs function, this paper designs a star-wheel stair-climbing mechanism. Through the effect of the lock coupling, the star-wheel stair-climbing mechanism is formed to be fixed axis gear train or planetary gear train achieving flat-walking and stair-climbing functions. Crossing obstacle analysis obtains the maximum height and minimum width of obstacle which the wheelchair can cross. Stress-strain analysis in Solidworks simulation is performed to verify material strength.
文摘This paper represented Autoregressive Neural Network (ARNN) and meant threshold methods for recognizing eye movements for control of an electrical wheelchair using EEG technology. The eye movements such as eyes open, eyes blinks, glancing left and glancing right related to a few areas of human brain were investigated. A Hamming low pass filter was applied to remove noise and artifacts of the eye signals and to extract the frequency range of the measured signals. An autoregressive model was employed to produce coefficients containing features of the EEG eye signals. The coefficients obtained were inserted the input layer of a neural network model to classify the eye activities. In addition, a mean threshold algorithm was employed for classifying eye movements. Two methods were compared to find the better one for applying in the wheelchair control to follow users to reach the desired direction. Experimental results of controlling the wheelchair in the indoor environment illustrated the effectiveness of the proposed approaches.
