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More than half of stroke patients live with different levels of motor dysfunction after receiving routine rehabilitation treatments. Therefore, new rehabilitation technologies are urgently needed as auxiliary treatments for motor rehabilitation. Based on routine rehabilitation treatments, a new intelligent rehabilitation platform has been developed for accurate evaluation of function and rehabilitation training. The emerging intelligent rehabilitation techniques can promote the development of motor function rehabilitation in terms of informatization, standardization, and intelligence. Traditional assessment methods are mostly subjective, depending on the experience and expertise of clinicians, and lack standardization and precision. It is therefore difficult to track functional changes during the rehabilitation process. Emerging intelligent rehabilitation techniques provide objective and accurate functional assessment for stroke patients that can promote improvement of clinical guidance for treatment. Artificial intelligence and neural networks play a critical role in intelligent rehabilitation. Multiple novel techniques, such as brain-computer interfaces, virtual reality, neural circuit-magnetic stimulation, and robot-assisted therapy, have been widely used in the clinic. This review summarizes the emerging intelligent rehabilitation techniques for the evaluation and treatment of motor dysfunction caused by nervous system diseases.

The lower limb exoskeleton provides assistance by following the lower limb joints’ desired motion trajectory. However, angle control is not enough to meet the requirements in some special circumstances such as encountering obstacles. In the swing phase of the attached leg with the exoskeleton, there is a different contact force between the sole and the road surface in different road conditions. Therefore, it is particularly important to control the joint angle and contact force simultaneously, that is, it is not only necessary to follow the desired angle but also to minimize the influence of external contact force. In this article, a novel scheme is proposed to adjust the trajectory dynamically in the swing phase. First of all, the physical model is streamlined and the Lagrangian principle is carried out to dynamic analysis and established a model of lower limb exoskeleton in the swing phase. Furthermore, the angle dynamics equation is transformed into a Cartesian coordinate system to calculate the end contact force for the impedance model. Finally, the impedance control strategy together with a disturbance observer is designed which is suitable for nonlinear and strong coupling characteristics. The simulation result shows that the control system can follow the angle accurately in the condition of minimizing external constraints. Hardware experiment shows that lower extremity exoskeleton can adjust motion trajectory actively when encountering obstacles and complete the movement trajectory tracking at the same time.

Older adults with mild cognitive impairment (MCI) have a high risk of developing Alzheimer’s disease. Gait performance is a potential clinical marker for the progression of MCI into dementia. However, the relationship between gait and brain functional connectivity (FC) in older adults with MCI remains unclear. Forty-five subjects [MCI group, n = 23; healthy control (HC) group, n = 22] were recruited. Each subject performed a walking task (Task 01), counting backward–walking task (Task 02), naming animals–walking task (Task 03), and calculating–walking task (Task 04). The gait parameters and cerebral oxygenation signals from the left prefrontal cortex (LPFC), right prefrontal cortex (RPFC), left motor cortex (LMC), right motor cortex (RMC), left occipital leaf cortex (LOL), and right occipital leaf cortex (ROL) were obtained simultaneously. Wavelet phase coherence was calculated in two frequency intervals: low frequency (interval I, 0.052–0.145 Hz) and very low frequency (interval II, 0.021–0.052 Hz). Results showed that the FC of RPFC–RMC is significantly lower in interval I in Task 03 compared with that in Task 02 in the MCI group (p = 0.001). Also, the right relative symmetry index (IDpsR) is significantly lower in Task 03 compared with that in Task 02 (p = 0.000). The IDpsR is positively correlated with the FC of RPFC–RMC in interval I in the MCI group (R = 0.205, p = 0.041). The gait symmetry such as left relative symmetry index (IDpsL) and IDpsR is significantly lower in the dual-task (DT) situation compared with the single task in the two groups (p < 0.05). The results suggested that the IDpsR might reflect abnormal change in FC of RPFC–RMC in interval I in the MCI population during Task 03. The gait symmetry is affected by DTs in both groups. The findings of this study may have a pivotal role in the early monitoring and intervention of brain dysfunction among older adults with MCI.

In the early 1990s, it has been described that LTα and LTβ form LTα2β and LTαβ2 heterotrimers, which bind to TNFR1 and LTβR, respectively. Afterwards, the LTαβ2–LTβR system has been intensively studied while the LTα2β–TNFR1 interaction has been ignored to date, presumably due to the fact that at the time of identification of the LTα2β–TNFR1 interaction one knew already two ligands for TNFR1, namely TNF and LTα. Here, we show that LTα2β interacts not only with TNFR1 but also with TNFR2. We furthermore demonstrate that membrane-bound LTα2β (memLTα2β), despite its asymmetric structure, stimulates TNFR1 and TNFR2 signaling. Not surprising in view of its ability to interact with TNFR2, LTα2β is inhibited by Etanercept, which is approved for the treatment of rheumatoid arthritis and also inhibits TNF and LTα.