Motor system uses muscle synergies as a modular organization to simplify the control of movements. Motor cortical impairments, such as stroke and spinal cord injuries, disrupt the orchestration of the muscle synergies and result in abnormal movements. In this paper, the alterations of muscle synergies in subacute stroke survivors were examined during the voluntary reaching movement. We collected electromyographic (EMG) data from 35 stroke survivors, ranging from Brunnstrom Stage III to VI, and 25 age-matched control subjects. Muscle synergies were extracted from the activity of 7 upper-limb muscles via nonnegative matrix factorization under the criterion of 95% variance accounted for. By comparing the structure of muscle synergies and the similarity of activation coefficients across groups, we can validate the increasing activation of pectoralis major muscle and the decreasing activation of elbow extensor of triceps in stroke groups. Furthermore, the similarity of muscle synergies was significantly correlated with the Brunnstrom Stage (R = 0.52, p < 0.01). The synergies of stroke survivors at Brunnstrom Stage IV–III gradually diverged from those of control group, but the activation coefficients remained the same after stroke, irrespective of the recovery level.

Background. Quantitative assessment of motor function is extremely important for poststroke patients as it can be used to develop personalized treatment strategies. This study aimed to propose an evaluation method for upper limb motor function in stroke patients. Methods. Thirty-four stroke survivors and twenty-five age-matched healthy volunteers as the control group were recruited for this study. Inertial sensor data and surface electromyography (sEMG) signals were collected from the upper limb during voluntary upward reaching. Five features included max shoulder joint angle, peak and average speeds, torso balance calculated from inertial sensor data, and muscle synergy similarity extracted from sEMG data by the nonnegative matrix factorization algorithm. Meanwhile, the Fugl–Meyer score of each patient was graded by professional rehabilitation therapist. Results. Statistically significant differences were observed among severe, mild-to-moderate, and control group of five features ( p   ≤  0.001). The features varied as the level of upper limb motor function changes since these features significantly correlated with the Fugl–Meyer assessment scale ( p   ≤  0.001). Moreover, the Bland–Altman method was conducted and showed high consistency between the evaluation method of five features and Fugl–Meyer scale. Therefore, the five features proposed in this paper can quantitatively evaluate the motor function of stroke patients which is very useful in the rehabilitation process.

Abstract. BACKGROUND: Nowadays, stroke is a leading cause of disability in adults. Assessment of motor performance has played an important role in rehabilitation for post stroke patients. Therefore, it is quite important to develop an automatic assessment system of motor function. OBJECTIVE: The purpose of this study is to assess the performance of the single task upper-limb movements quantitatively among stroke survivors. METHODS: Eleven normal subjects and thirty-five subjects with stroke were involved in this study. The subjects, who were wearing the micro-sensor motion capture system, performed shoulder flexion in a sitting position. The system recorded threedimensional kinematics data of limb movements in quaternions. By extracting the significant features from these data, we built a linear model to acquire the functional assessment score (FAS). RESULTS: All of the kinematics features have a significant statistical difference (P < 0.05) between patients and healthy people, while the feature values have a high correlation with Fugl-Meyer (FM) scores (r > 0.5, p < 0.05), indicating that these features are able to reflect the level of motion impairment. Furthermore, most samples of the linear model locate in the confidence interval after regression, with the residual approaching a normal distribution. These results show that the FAS is capable of motor function assessment for stroke survivors. CONCLUSION: These findings represent an important step towards a system that can be utilized for precise single task motor evaluation after stroke, applicable to clinical research and as a tool for rehabilitation.

This paper proposes a neuromusculoskeletal (NMS) model to predict individual muscle force during elbow flexion and extension. Four male subjects were asked to do voluntary elbow flexion and extension. An inertial sensor and surface electromyography (sEMG) sensors were attached to subject's forearm. Joint angle calculated by fusion of acceleration and angular rate using an extended Kalman filter (EKF) and muscle activations obtained from the sEMG signals were taken as the inputs of the proposed NMS model to determine individual muscle force. The result shows that our NMS model can predict individual muscle force accurately, with the ability to reflect subject-specific joint dynamics and neural control solutions. Our method incorporates sEMG and motion data, making it possible to get a deeper understanding of neurological, physiological, and anatomical characteristics of human dynamic movement. We demonstrate the potential of the proposed NMS model for evaluating the function of upper limb movements in the field of neurorehabilitation.

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The Fenwei Plain plays an essential role for China’s three-year action plan to protect the air environment. At present, the high-value area and maximum value of atmospheric aerosol have been effectively controlled, but the governance situation is not stable. Therefore, based on the daily ultraviolet aerosol index (UVAI) data retrieved by Ozone Monitoring Instrument (OMI) from 2012 to 2020, combined with precipitation and temperature and air pressure and lifting index data, this paper analyzes the spatiotemporal distribution characteristics and some influencing factors of UVAI in the Fenwei Plain. The results show that the overall trend of the annual average UVAI value of the Fenwei Plain in 9 years showed two “peaks” in 2013 and 2018, respectively. The high UVAI values are mainly concentrated in the southwest and central areas of the Fenwei Plain. In the study area, UVAI was highest in winter, followed by autumn and spring, and lowest in summer. There were significant negative correlations between precipitation and UVAI and between temperature and UVAI. There were significant positive correlations between air pressure and UVAI and between lifting index and UVAI. According to the backward trajectory clustering results, during the autumn and winter seasons in this area, due to the sand and dust brought by the northwest and the input of aerosols in the coal-producing area and coal-fired heating area, the UVAI value of this time period is higher.