Closed-Loop Wearable Device Network of Intrinsically-Controlled, Bilateral Coordinated Functional Electrical Stimulation for Stroke.

Innovative functional electrical stimulation has demonstrated effectiveness in enhancing daily walking and rehabilitating stroke patients with foot drop. However, its lack of precision in stimulating timing, individual adaptivity, and bilateral symmetry, resulted in diminished clinical efficacy. Therefore, a closed-loop wearable device network of intrinsically controlled functional electrical stimulation (CI-FES) system is proposed, which utilizes the personal surface myoelectricity, derived from the intrinsic neuro signal, as the switch to activate/deactivate the stimulation on the affected side. Simultaneously, it decodes the myoelectricity signal of the patient's healthy side to adjust the stimulation intensity, forming an intrinsically controlled loop with the inertial measurement units. With CI-FES assistance, patients' walking ability significantly improved, evidenced by the shift in ankle joint angle mean and variance from 105.53° and 28.84 to 102.81° and 17.71, and the oxyhemoglobin concentration tested by the functional near-infrared spectroscopy. In long-term CI-FES-assisted clinical testing, the discriminability in machine learning classification between patients and healthy individuals gradually decreased from 100% to 92.5%, suggesting a remarkable recovery tendency, further substantiated by performance on the functional movement scales. The developed CI-FES system is crucial for contralateral-hemiplegic stroke recovery, paving the way for future closed-loop stimulation systems in stroke rehabilitation is anticipated.

Comparison of different machine learning classification models for predicting deep vein thrombosis in lower extremity fractures.

Deep vein thrombosis (DVT) is a common complication in patients with lower extremity fractures. Once it occurs, it will seriously affect the quality of life and postoperative recovery of patients. Therefore, early prediction and prevention of DVT can effectively improve the prognosis of patients. This study constructed different machine learning models to explore their effectiveness in predicting DVT. Five prediction models were applied to the study, including Extreme Gradient Boosting (XGBoost) model, Logistic Regression (LR) model, RandomForest (RF) model, Multilayer Perceptron (MLP) model, and Support Vector Machine (SVM) model. Afterwards, the performance of the obtained prediction models was evaluated by area under the curve (AUC), accuracy, sensitivity, specificity, F1 score, and Kappa. The prediction performances of the models based on machine learning are as follows: XGBoost model (AUC = 0.979, accuracy = 0.931), LR model (AUC = 0.821, accuracy = 0.758), RF model (AUC = 0.970, accuracy = 0.921), MLP model (AUC = 0.830, accuracy = 0.756), SVM model (AUC = 0.713, accuracy = 0.661). On our data set, the XGBoost model has the best performance. However, the model still needs external verification research before clinical application.

Interference of unilateral lower limb amputation on motor imagery rhythm and remodeling of sensorimotor areas.

Purpose: The effect of sensorimotor stripping on neuroplasticity and motor imagery capacity is unknown, and the physiological mechanisms of post-amputation phantom limb pain (PLP) illness remain to be investigated. Materials and methods: In this study, an electroencephalogram (EEG)-based event-related (de)synchronization (ERD/ERS) analysis was conducted using a bilateral lower limb motor imagery (MI) paradigm. The differences in the execution of motor imagery tasks between left lower limb amputations and healthy controls were explored, and a correlation analysis was calculated between level of phantom limb pain and ERD/ERS. Results: The multiple frequency bands showed a significant ERD phenomenon when the healthy control group performed the motor imagery task, whereas amputees showed significant ERS phenomena in mu band. Phantom limb pain in amputees was negatively correlated with bilateral sensorimotor areas electrode powers. Conclusion: Sensorimotor abnormalities reduce neural activity in the sensorimotor cortex, while the motor imagination of the intact limb is diminished. In addition, phantom limb pain may lead to over-activation of sensorimotor areas, affecting bilateral sensorimotor area remodeling.

Altered cortical activity in patients with lower limb amputation based on EEG microstate.

Previous studies have revealed significant changes in electroencephalogram (EEG) microstates in neuropsychiatric diseases, including schizophrenia, depression, and dementia. To explore the resting-state EEG microstate with amputation, we collected the EEG datasets from 15 patients with lower limb amputation and 20 healthy controls. Then, we analyzed the parameters of four classical EEG microstates (A-D) between the two groups. Specifically, the parameters were statistically analyzed, including duration, occurrence rate, time coverage, and transition rate. According to the results, the duration of microstate C (t = 2.95, p = 0.005) in the lower limb amputation group was significantly smaller compared with the control group, while the occurrence rate of microstate B (t = -2.22, p = 0.03) and D (t = -3.35, p = 0.002) were significantly larger in the lower limb amputation group. In addition, the transition rate of microstate differed significantly in AC, CA, DB between the two groups. Our results implied: (1) amputation has changed the resting-state EEG microstate; (2) EEG microstate analysis can be an approach to explore the alteration of cortical function.

[A experiment research of beryllium oxide induced oxidative lung injury and the protective effects of LBP in rats].

OBJECTIVE: To explore beryllium oxide induced oxidative lung injury and the protective effects of LBP. METHODS: Intoxication of animals were induced by once intratracheal injection and LBP intervention by intragastric administration. The content of HIF-1, VEGF and HO-1 of lung tissues were measured by kits. The pathological changes of lung tissue were showed by pathological section. The changes of lung ultrastructure were observed by electron microscope. RESULTS: Pathological changes of the lung tissue in beryllium oxide exposure group rats were in line with the characteristics of beryllium disease in human. Compared with the control group, HO-1 was increased in beryllium oxide exposure 40 d group and low doses of LBP group, compared with the control group, HO-1 was increased in beryllium oxide exposure 80d group and LBP treatment groups (P < 0.05 or P < 0.01). Compared with the control group, HIF-1 was increased in beryllium oxide exposure 40 d group, LBP treatment groups, beryllium oxide exposure 60 d and 80 d groups (P < 0.05 or P < 0.01). Compared with the control group, VEGF was increased of all phases, especially in beryllium oxide exposure 40d and 80 groups, LBP treatment groups and beryllium oxide exposure 60 d (P < 0.05 or P < 0.01). The content of HO-1 of beryllium oxide exposure group was higher than the LBP treatment for 40d group but below LBP treatment for 80 d group (P < 0.05). The content of HIF1 of beryllium oxide exposure group was higher than high dose of LBP treatment for 60d group and LBP treatment for 80 d group (P < 0.01). The content of VEGF of beryllium oxide exposure group was higher than LBP treatment for 40 d group and high dose of LBP treatment for 60 d (P < 0.05 or P < 0.01). CONCLUSIONS: BeO can cause abnormal expression of related genes of lung tissue in rats, LBP has protective effects on BeO caused lung injury.