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Luo S, Meng Q, Li S, Yu H. Research of intent recognition in rehabilitation robots: a systematic review. Disabil Rehabil Assist Technol 2024; 19:1307-1318. [PMID: 36695473 DOI: 10.1080/17483107.2023.2170477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 01/10/2023] [Accepted: 01/16/2023] [Indexed: 01/26/2023]
Abstract
PURPOSE Rehabilitation robots with intent recognition are helping people with dysfunction to enjoy better lives. Many rehabilitation robots with intent recognition have been developed by academic institutions and commercial companies. However, there is no systematic summary about the application of intent recognition in the field of rehabilitation robots. Therefore, the purpose of this paper is to summarize the application of intent recognition in rehabilitation robots, analyze the current status of their research, and provide cutting-edge research directions for colleagues. MATERIALS AND METHODS Literature searches were conducted on Web of Science, IEEE Xplore, ScienceDirect, SpringerLink, and Medline. Search terms included "rehabilitation robot", "intent recognition", "exoskeleton", "prosthesis", "surface electromyography (sEMG)" and "electroencephalogram (EEG)". References listed in relevant literature were further screened according to inclusion and exclusion criteria. RESULTS In this field, most studies have recognized movement intent by kinematic, sEMG, and EEG signals. However, in practical studies, the development of intent recognition in rehabilitation robots is limited by the hysteresis of kinematic signals and the weak anti-interference ability of sEMG and EEG signals. CONCLUSIONS Intent recognition has achieved a lot in the field of rehabilitation robotics but the key factors limiting its development are still timeliness and accuracy. In the future, intent recognition strategy with multi-sensor information fusion may be a good solution.
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Affiliation(s)
- Shengli Luo
- Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai, China
| | | | - Sujiao Li
- Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai, China
| | - Hongliu Yu
- Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai, China
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Tian J, Wang H, Lu H, Yang Y, Li L, Niu J, Cheng B. Force/position-based velocity control strategy for the lower limb rehabilitation robot during active training: design and validation. Front Bioeng Biotechnol 2024; 11:1335071. [PMID: 38260744 PMCID: PMC10800786 DOI: 10.3389/fbioe.2023.1335071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 12/20/2023] [Indexed: 01/24/2024] Open
Abstract
Aiming at the shortcomings of most existing control strategies for lower limb rehabilitation robots that are difficult to guarantee trajectory tracking effect and active participation of the patient, this paper proposes a force/position-based velocity control (FPVC) strategy for the hybrid end-effector lower limb rehabilitation robot (HE-LRR) during active training. The configuration of HE-LRR is described and the inverse Jacobian analysis is carried out. Then, the FPVC strategy design is introduced in detail, including normal velocity planning and tangential velocity planning. The experimental platform for the HE-LRR system is presented. A series of experiments are conducted to validate the FPVC strategy's performance, including trajectory measurement experiments, force and velocity measurement experiments, and active participation experiments. Experimental studies show that the end effector possesses good following performance with the reference trajectory and the desired velocity, and the active participation of subjects can be adjusted by the control strategy parameters. The experiments have verified the rationality of the FPVC strategy, which can meet the requirements of trajectory tracking effect and active participation, indicating its good application prospects in the patient's robot-assisted active training.
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Affiliation(s)
- Junjie Tian
- Hebei Provincial Key Laboratory of Parallel Robot and Mechatronic System, Yanshan University, Qinhuangdao, China
- School of Mechanical Engineering, Yanshan University, Qinhuangdao, China
| | - Hongbo Wang
- Hebei Provincial Key Laboratory of Parallel Robot and Mechatronic System, Yanshan University, Qinhuangdao, China
- School of Mechanical Engineering, Yanshan University, Qinhuangdao, China
- Academy for Engineering and Technology, Fudan University, Shanghai, China
| | - Hao Lu
- Academy for Engineering and Technology, Fudan University, Shanghai, China
| | - Yang Yang
- Hebei Provincial Key Laboratory of Parallel Robot and Mechatronic System, Yanshan University, Qinhuangdao, China
- School of Mechanical Engineering, Yanshan University, Qinhuangdao, China
| | - Lianqing Li
- Hebei Provincial Key Laboratory of Parallel Robot and Mechatronic System, Yanshan University, Qinhuangdao, China
- School of Mechanical Engineering, Yanshan University, Qinhuangdao, China
| | - Jianye Niu
- Hebei Provincial Key Laboratory of Parallel Robot and Mechatronic System, Yanshan University, Qinhuangdao, China
- School of Mechanical Engineering, Yanshan University, Qinhuangdao, China
| | - Bo Cheng
- Qinhuangdao Hospital of Traditional Chinese Medicine, Qinhuangdao, China
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Dordevic M, Maile O, Das A, Kundu S, Haun C, Baier B, Müller NG. A Comparison of Immersive vs. Non-Immersive Virtual Reality Exercises for the Upper Limb: A Functional Near-Infrared Spectroscopy Pilot Study with Healthy Participants. J Clin Med 2023; 12:5781. [PMID: 37762722 PMCID: PMC10531854 DOI: 10.3390/jcm12185781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 08/21/2023] [Accepted: 08/28/2023] [Indexed: 09/29/2023] Open
Abstract
Functional near-infrared spectroscopy (fNIRS) allows for a reliable assessment of oxygenated blood flow in relevant brain regions. Recent advancements in immersive virtual reality (VR)-based technology have generated many new possibilities for its application, such as in stroke rehabilitation. In this study, we asked whether there is a difference in oxygenated hemoglobin (HbO2) within brain motor areas during hand/arm movements between immersive and non-immersive VR settings. Ten healthy young participants (24.3 ± 3.7, three females) were tested using a specially developed VR paradigm, called "bus riding", whereby participants used their hand to steer a moving bus. Both immersive and non-immersive conditions stimulated brain regions controlling hand movements, namely motor cortex, but no significant differences in HbO2 could be found between the two conditions in any of the relevant brain regions. These results are to be interpreted with caution, as only ten participants were included in the study.
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Affiliation(s)
- Milos Dordevic
- Department of Chronic and Degenerative Diseases, Faculty of Health Sciences (FGW), Potsdam University, 14476 Potsdam, Germany
- Department of Neurology, Otto-von-Guericke University, 39120 Magdeburg, Germany
| | - Olga Maile
- Department of Neurology, Otto-von-Guericke University, 39120 Magdeburg, Germany
| | - Anustup Das
- Faculty of Informatics, Otto-von-Guericke University, 39106 Magdeburg, Germany
| | - Sumit Kundu
- Department of Chronic and Degenerative Diseases, Faculty of Health Sciences (FGW), Potsdam University, 14476 Potsdam, Germany
- Faculty of Informatics, Otto-von-Guericke University, 39106 Magdeburg, Germany
| | - Carolin Haun
- Edith-Stein Fachklinik, 76887 Bad Bergzabern, Germany
| | - Bernhard Baier
- Edith-Stein Fachklinik, 76887 Bad Bergzabern, Germany
- University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Notger G. Müller
- Department of Chronic and Degenerative Diseases, Faculty of Health Sciences (FGW), Potsdam University, 14476 Potsdam, Germany
- Department of Neurology, Otto-von-Guericke University, 39120 Magdeburg, Germany
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Du J, Shi P, Liu J, Yu H, Fang F. Analgesic Electrical Stimulation Combined with Wrist-Ankle Acupuncture Reduces the Cortical Response to Pain in Patients with Myofasciitis: A Randomized Clinical Trial. PAIN MEDICINE 2023; 24:351-361. [PMID: 36102803 DOI: 10.1093/pm/pnac141] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 07/21/2022] [Accepted: 09/01/2022] [Indexed: 11/13/2022]
Abstract
OBJECTIVE Transcutaneous electrical nerve stimulation (TENS) based on wrist-ankle acupuncture has been shown to relieve pain levels in patients with myofascial pain syndrome (MPS). However, its efficacy is highly subjective. The purpose of this study was to evaluate the feasibility and effectiveness of TENS based on wrist-ankle acupuncture for pain management in patients with MPS from the perspective of cerebral cortex hemodynamics. DESIGN, SETTING, PARTICIPANTS AND INTERVENTIONS We designed a double-blind, randomized, controlled clinical trial. Thirty-one male patients with MPS were randomly assigned to two parallel groups. The experimental group (n = 16) received TENS based on wrist-ankle acupuncture for analgesic treatment, while the control group (n = 15) did not. The pain was induced by mechanically pressurized at acupoint Jianjing. The multichannel functional near-infrared spectroscopy (fNIRS) equipment was utilized for measuring oxyhemoglobin (HbO) levels in the cerebral cortex during the tasks. RESULTS After the intervention, visual analog scale (VAS), the activation degree and activation area of pain perception cortices were significantly reduced in the experimental group compared to the baseline values (P < .05). Particularly, Frontopolar Area (FPA), and Dorsolateral Prefrontal Cortex (DLPFC) are highly involved in the pain process and pain modulation. CONCLUSION Compared to no intervention, TENS based on wrist-ankle acupuncture can be effective in relieving pain in patients with MPS in terms of cerebral cortical hemodynamics. However, further studies are necessary to quantify the analgesic effect in terms of cerebral hemodynamics and brain activation.
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Affiliation(s)
- Jiahao Du
- Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai, China
| | - Ping Shi
- Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai, China
| | - Junwen Liu
- Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai, China
| | - Hongliu Yu
- Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai, China
| | - Fanfu Fang
- Changhai Hospital, Naval Medical University, Shanghai, China
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Zheng J, He W, Ma Q, Cai W, Li S, Yu H. Cortical activation in robot-assisted dynamic and static resistance training combining VR interaction: An fNIRS based pilot study. NeuroRehabilitation 2023; 52:413-423. [PMID: 36806524 DOI: 10.3233/nre-220292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/19/2023]
Abstract
BACKGROUND There are few isometric training systems based on upper limb rehabilitation robots. Its efficacy and neural mechanism are not well understood. OBJECTIVE This study aims to investigate the cortex activation of dynamic resistance and static (isometric) training based on upper limb rehabilitation robot combined with virtual reality (VR) interaction by using functional near-infrared spectroscopy (fNIRS). METHODS Twenty subjects were included in this study. The experiment adopts the block paradigm design. Experiment in dynamic and static conditions consisted of three trials, each consisting of task (60 s)-rest (40 s). The neural activities of the sensorimotor cortex (SMC), premotor cortex (PMC) and prefrontal cortex (PFC) were measured. The cortex activation and functional connectivity (FC) were analyzed. RESULTS Both the dynamic and static training can activate SMC, PMC, and PFC. In SMC and PMC, the activation of static training was stronger than dynamic training, there were significant differences between the two modes of each region of interest (ROI) (p < 0.05) (SMC: p = 0.022, ES = 0.72, PMC: p = 0.039, ES = 0.63). Besides, the FC between all ROIs of the static training was stronger than that of the dynamic training. CONCLUSION The static training based on upper limb rehabilitation robot may better facilitate the cortical activation associated with motor control.
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Affiliation(s)
- Jinyu Zheng
- Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai, China.,Shanghai Engineering Research Center of Assistive Devices, Shanghai, China
| | - Wanying He
- Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai, China.,Shanghai Engineering Research Center of Assistive Devices, Shanghai, China
| | - Qiqi Ma
- Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai, China.,Shanghai Engineering Research Center of Assistive Devices, Shanghai, China
| | - Wenqian Cai
- Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai, China.,Shanghai Engineering Research Center of Assistive Devices, Shanghai, China
| | - Sujiao Li
- Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai, China.,Shanghai Engineering Research Center of Assistive Devices, Shanghai, China.,Key Laboratory of Neural-Functional Information and Rehabilitation Engineering of the Ministry of Civil Affairs, Shanghai, China
| | - Hongliu Yu
- Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai, China.,Shanghai Engineering Research Center of Assistive Devices, Shanghai, China.,Key Laboratory of Neural-Functional Information and Rehabilitation Engineering of the Ministry of Civil Affairs, Shanghai, China
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Li Y, Xu Z, Xie H, Fu R, Lo WLA, Cheng X, Yang J, Ge L, Yu Q, Wang C. Changes in cortical activation during upright stance in individuals with chronic low back pain: An fNIRS study. Front Hum Neurosci 2023; 17:1085831. [PMID: 36816497 PMCID: PMC9936824 DOI: 10.3389/fnhum.2023.1085831] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 01/17/2023] [Indexed: 02/05/2023] Open
Abstract
Introduction Postural control deficits are a potential cause of persistent and recurrent pain in patients with chronic low back pain (CLBP). Although some studies have confirmed that the dorsolateral prefrontal cortex (DLPFC) contributes to pain regulation in CLBP, its role in the postural control of patients with CLBP remains unclear. Therefore, this study aimed to investigate the DLPFC activation of patients with CLBP and healthy controls under different upright stance task conditions. Methods Twenty patients with CLBP (26.50 ± 2.48 years) and 20 healthy controls (25.75 ± 3.57 years) performed upright stance tasks under three conditions: Task-1 was static balance with eyes open; Task-2 was static balance with eyes closed; Task-3 involved dynamic balance on an unstable surface with eyes open. A wireless functional near-infrared spectroscopy (fNIRS) system measured cortical activity, including the bilateral DLPFC, pre-motor cortex (PMC) and supplementary motor area (SMA), the primary motor cortex (M1), the primary somatosensory cortex (S1), and a force platform measured balance parameters during upright stance. Results The two-way repeated measures ANOVA results showed significant interaction in bilateral PMC/SMA activation. Moreover, patients with CLBP had significantly increased right DLPFC activation and higher sway 32 area and velocity than healthy controls during upright stance. Discussion Our results imply that PMC/SMA and DLPFC maintain standing balance. The patients with CLBP have higher cortical activity and upright stance control deficits, which may indicate that the patients with CLBP have low neural efficiency and need more motor resources to maintain balance.
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Wang D, Huang Y, Liang S, Meng Q, Yu H. The identification of interacting brain networks during robot-assisted training with multimodal stimulation. J Neural Eng 2023; 20. [PMID: 36548992 DOI: 10.1088/1741-2552/acae05] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Accepted: 12/22/2022] [Indexed: 12/24/2022]
Abstract
Objective.Robot-assisted rehabilitation training is an effective way to assist rehabilitation therapy. So far, various robotic devices have been developed for automatic training of central nervous system following injury. Multimodal stimulation such as visual and auditory stimulus and even virtual reality technology were usually introduced in these robotic devices to improve the effect of rehabilitation training. This may need to be explained from a neurological perspective, but there are few relevant studies.Approach.In this study, ten participants performed right arm rehabilitation training tasks using an upper limb rehabilitation robotic device. The tasks were completed under four different feedback conditions including multiple combinations of visual and auditory components: auditory feedback; visual feedback; visual and auditory feedback (VAF); non-feedback. The functional near-infrared spectroscopy devices record blood oxygen signals in bilateral motor, visual and auditory areas. Using hemoglobin concentration as an indicator of cortical activation, the effective connectivity of these regions was then calculated through Granger causality.Main results.We found that overall stronger activation and effective connectivity between related brain regions were associated with VAF. When participants completed the training task without VAF, the trends in activation and connectivity were diminished.Significance.This study revealed cerebral cortex activation and interacting networks of brain regions in robot-assisted rehabilitation training with multimodal stimulation, which is expected to provide indicators for further evaluation of the effect of rehabilitation training, and promote further exploration of the interaction network in the brain during a variety of external stimuli, and to explore the best sensory combination.
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Affiliation(s)
- Duojin Wang
- Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai 200093, People's Republic of China.,Shanghai Engineering Research Center of Assistive Devices, 516 Jungong Road, Shanghai 200093, People's Republic of China
| | - Yanping Huang
- Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai 200093, People's Republic of China
| | - Sailan Liang
- Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai 200093, People's Republic of China
| | - Qingyun Meng
- College of Rehabilitation Sciences, Shanghai University of Medicine & Health Sciences, 279 Zhouzhu Road, Shanghai 201318, People's Republic of China
| | - Hongliu Yu
- Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai 200093, People's Republic of China.,Shanghai Engineering Research Center of Assistive Devices, 516 Jungong Road, Shanghai 200093, People's Republic of China
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Du Q, Luo J, Cheng Q, Wang Y, Guo S. Vibrotactile enhancement in hand rehabilitation has a reinforcing effect on sensorimotor brain activities. Front Neurosci 2022; 16:935827. [PMID: 36267238 PMCID: PMC9577243 DOI: 10.3389/fnins.2022.935827] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Accepted: 08/31/2022] [Indexed: 11/13/2022] Open
Abstract
Objective Stroke patients often suffer from hand dysfunction or loss of tactile perception, which in turn interferes with hand rehabilitation. Tactile-enhanced multi-sensory feedback rehabilitation is an approach worth considering, but its effectiveness has not been well studied. By using functional near-infrared spectroscopy (fNIRS) to analyze the causal activity patterns in the sensorimotor cortex, the present study aims to investigate the cortical hemodynamic effects of hand rehabilitation training when tactile stimulation is applied, and to provide a basis for rehabilitation program development. Methods A vibrotactile enhanced pneumatically actuated hand rehabilitation device was tested on the less-preferred hand of 14 healthy right-handed subjects. The training tasks consisted of move hand and observe video (MO), move hand and vibration stimulation (MV), move hand, observe video, and vibration stimulation (MOV), and a contrast resting task. Region of interest (ROI), a laterality index (LI), and causal brain network analysis methods were used to explore the brain’s cortical blood flow response to a multi-sensory feedback rehabilitation task from multiple perspectives. Results (1) A more pronounced contralateral activation in the right-brain region occurred under the MOV stimulation. Rehabilitation tasks containing vibrotactile enhancement (MV and MOV) had significantly more oxyhemoglobin than the MO task at 5 s after the task starts, indicating faster contralateral activation in sensorimotor brain regions. (2) Five significant lateralized channel connections were generated under the MV and MOV tasks (p < 0.05), one significant lateralized channel connection was generated by the MO task, and the Rest were not, showing that MV and MOV caused stronger lateralization activation. (3) We investigated all thresholds of granger causality (GC) resulting in consistent relative numbers of effect connections. MV elicited stronger causal interactions between the left and right cerebral hemispheres, and at the GC threshold of 0.4, there were 13 causal network connection pairs for MV, 7 for MO, and 9 for MOV. Conclusion Vibrotactile cutaneous stimulation as a tactile enhancement can produce a stronger stimulation of the brain’s sensorimotor brain areas, promoting the establishment of neural pathways, and causing a richer effect between the left and right cerebral hemispheres. The combination of kinesthetic, vibrotactile, and visual stimulation can achieve a more prominent training efficiency from the perspective of functional cerebral hemodynamics.
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Affiliation(s)
- Qiang Du
- Academy for Engineering and Technology, Fudan University, Shanghai, China
- Shanghai Engineering Research Center of AI and Robotics, Shanghai, China
- Engineering Research Center of AI and Robotics, Ministry of Education, Shanghai, China
| | - Jingjing Luo
- Academy for Engineering and Technology, Fudan University, Shanghai, China
- Shanghai Engineering Research Center of AI and Robotics, Shanghai, China
- Engineering Research Center of AI and Robotics, Ministry of Education, Shanghai, China
- Jihua Laboratory, Foshan, China
- *Correspondence: Jingjing Luo,
| | - Qiying Cheng
- Academy for Engineering and Technology, Fudan University, Shanghai, China
- Shanghai Engineering Research Center of AI and Robotics, Shanghai, China
- Engineering Research Center of AI and Robotics, Ministry of Education, Shanghai, China
| | - Youhao Wang
- Academy for Engineering and Technology, Fudan University, Shanghai, China
- Shanghai Engineering Research Center of AI and Robotics, Shanghai, China
- Engineering Research Center of AI and Robotics, Ministry of Education, Shanghai, China
| | - Shijie Guo
- Academy for Engineering and Technology, Fudan University, Shanghai, China
- Shanghai Engineering Research Center of AI and Robotics, Shanghai, China
- Engineering Research Center of AI and Robotics, Ministry of Education, Shanghai, China
- Department of the State Key Laboratory of Reliability and Intelligence of Electrical Equipment and the Hebei Key Laboratory of Robot Perception and Human-Robot Interaction, Hebei University of Technology, Tianjin, China
- Shijie Guo,
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A neurophysiologically interpretable deep neural network predicts complex movement components from brain activity. Sci Rep 2022; 12:1101. [PMID: 35058514 PMCID: PMC8776813 DOI: 10.1038/s41598-022-05079-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 12/31/2021] [Indexed: 12/03/2022] Open
Abstract
The effective decoding of movement from non-invasive electroencephalography (EEG) is essential for informing several therapeutic interventions, from neurorehabilitation robots to neural prosthetics. Deep neural networks are most suitable for decoding real-time data but their use in EEG is hindered by the gross classes of motor tasks in the currently available datasets, which are solvable even with network architectures that do not require specialized design considerations. Moreover, the weak association with the underlying neurophysiology limits the generalizability of modern networks for EEG inference. Here, we present a neurophysiologically interpretable 3-dimensional convolutional neural network (3D-CNN) that captured the spatiotemporal dependencies in brain areas that get co-activated during movement. The 3D-CNN received topography-preserving EEG inputs, and predicted complex components of hand movements performed on a plane using a back-drivable rehabilitation robot, namely (a) the reaction time (RT) for responding to stimulus (slow or fast), (b) the mode of movement (active or passive, depending on whether there was an assistive force provided by the apparatus), and (c) the orthogonal directions of the movement (left, right, up, or down). We validated the 3D-CNN on a new dataset that we acquired from an in-house motor experiment, where it achieved average leave-one-subject-out test accuracies of 79.81%, 81.23%, and 82.00% for RT, active vs. passive, and direction classifications, respectively. Our proposed method outperformed the modern 2D-CNN architecture by a range of 1.1% to 6.74% depending on the classification task. Further, we identified the EEG sensors and time segments crucial to the classification decisions of the network, which aligned well with the current neurophysiological knowledge on brain activity in motor planning and execution tasks. Our results demonstrate the importance of biological relevance in networks for an accurate decoding of EEG, suggesting that the real-time classification of other complex brain activities may now be within our reach.
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Shi P, Li A, Yu H. Response of the Cerebral Cortex to Resistance and Non-resistance Exercise Under Different Trajectories: A Functional Near-Infrared Spectroscopy Study. Front Neurosci 2021; 15:685920. [PMID: 34720845 PMCID: PMC8548375 DOI: 10.3389/fnins.2021.685920] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Accepted: 09/16/2021] [Indexed: 12/19/2022] Open
Abstract
Background: At present, the effects of upper limb movement are generally evaluated from the level of motor performance. The purpose of this study is to evaluate the response of the cerebral cortex to different upper limb movement patterns from the perspective of neurophysiology. Method: Thirty healthy adults (12 females, 18 males, mean age 23.9 ± 0.9 years) took resistance and non-resistance exercises under four trajectories (T1: left and right straight-line movement; T2: front and back straight-line movement; T3: clockwise and anticlockwise drawing circle movement; and T4: clockwise and anticlockwise character ⁕ movement). Each movement included a set of periodic motions composed of a 30-s task and a 30-s rest. Functional near-infrared spectroscopy (fNIRS) was used to measure cerebral blood flow dynamics. Primary somatosensory cortex (S1), supplementary motor area (SMA), pre-motor area (PMA), primary motor cortex (M1), and dorsolateral prefrontal cortex (DLPFC) were chosen as regions of interests (ROIs). Activation maps and symmetric heat maps were applied to assess the response of the cerebral cortex to different motion patterns. Result: The activation of the brain cortex was significantly increased during resistance movement for each participant. Specifically, S1, SMA, PMA, and M1 had higher participation during both non-resistance movement and resistance movement. Compared to non-resistance movement, the resistance movement caused an obvious response in the cerebral cortex. The task state and the resting state were distinguished more obviously in the resistance movement. Four trajectories can be distinguished under non-resistance movement. Conclusion: This study confirmed that the response of the cerebral motor cortex to different motion patterns was different from that of the neurophysiological level. It may provide a reference for the evaluation of resistance training effects in the future.
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Affiliation(s)
- Ping Shi
- Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai, China
| | - Anan Li
- Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai, China
| | - Hongliu Yu
- Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai, China.,Shanghai Engineering Research Center of Assistive Devices, Shanghai, China
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