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Rehabilitation training and movement evaluation after stroke have become a research hotspot as stroke has become a very common and harmful disease. However, traditional rehabilitation training and evaluation are mainly conducted under the guidance of rehabilitation doctors. The evaluation process is time-consuming and the evaluation results are greatly influenced by doctors. In this study, a desktop upper limb rehabilitation robot was designed and a quantitative evaluation system of upper limb motor function for stroke patients was proposed. The kinematics and dynamics data of stroke patients during active training were collected by sensors. Combined with the scores of patients’ upper limb motor function by rehabilitation doctors using the Wolf Motor Function Test (WMFT) scale, three different quantitative evaluation models of upper limb motor function based on Back Propagation Neural Network (BPNN), K-Nearest Neighbors (KNN), and Support Vector Regression (SVR) algorithms were established. To verify the effectiveness of the quantitative evaluation system, 10 healthy subjects and 21 stroke patients were recruited for experiments. The experimental results show that the BPNN model has the best evaluation performance among the three quantitative evaluation models. The scoring accuracy of the BPNN model reached up to 87.1%. Moreover, there was a significant correlation between the models′ scores and the doctors′ scores. The proposed system can help doctors to quantitatively evaluate the upper limb motor function of stroke patients and accurately master the rehabilitation progress of patients.

The multi-carrier code division multiple access (MC-CDMA) technique is a promising technology because it incorporates the benefits of the orthogonal frequency division multiplexing (OFDM) and the direct sequence code division multiple access (DS-CDMA) techniques. The bit error rate (BER) of the MC-CDMA system reduces more quickly than that of the OFDM system when increasing the transmission power. In this paper, we propose a novel frequency-domain oversampling (FDO) minimum mean square error (MMSE) receiver for the cyclic prefix (CP) MC-CDMA. Simulation results show that the proposed FDO based receiver for the CP MC-CDMA systems can outperform the traditional zero forcing (ZF) and MMSE equalizers in terms of BER performance for all the spreading factors (SF).Index Terms-Multi-carrier CDMA, frequency domain oversampling, MMSE detection.