Motor imagery (MI) based brain-computer interfaces (BCI) extract commands in real-time and can be used to control a cursor, a robot or functional electrical stimulation (FES) devices. The control of FES devices is especially interesting for stroke rehabilitation, when a patient can use motor imagery to stimulate specific muscles in real-time. However, damage to motor areas resulting from stroke or other causes might impair control of a motor imagery BCI for rehabilitation. The current work presents a comparative evaluation of the MI-based BCI control accuracy between stroke patients and healthy subjects. Five patients who had a stroke that affected the motor system participated in the current study, and were trained across 10-24 sessions lasting about 1 h each with the recoveriX system. The participants' EEG data were classified while they imagined left or right hand movements, and real-time feedback was provided on a monitor. If the correct imagination was detected, the FES was also activated to move the left or right hand. The grand average mean accuracy was 87.4% for all patients and sessions. All patients were able to achieve at least one session with a maximum accuracy above 96%. Both the mean accuracy and the maximum accuracy were surprisingly high and above results seen with healthy controls in prior studies. Importantly, the study showed that stroke patients can control a MI BCI system with high accuracy relative to healthy persons. This may occur because these patients are highly motivated to participate in a study to improve their motor functions. Participants often reported early in the training of motor improvements and this caused additional motivation. However, it also reflects the efficacy of combining motor imagination, seeing continuous bar feedback, and real hand movement that also activates the tactile and proprioceptive systems. Results also suggested that motor function could improve even if classification accuracy did not, and suggest other new questions to explore in future work. Future studies will also be done with a first-person view 3D avatar to provide improved feedback and thereby increase each patients' sense of engagement.
The cardiovascular system is regulated by the autonomic nervous system, under cortical modulation. Stroke can induce cardiac autonomic imbalance, therefore, causing secondary cardiovascular complications. Heart rate variability (HRV) analysis is a simple method to appraise the autonomic nervous function. The purpose of this study was to investigate the cardiac autonomic activity in patients that suffered an ischemic stroke in middle cerebral artery (MCA) territory. Using Biopac Acquisition System, we monitored ECG in rest condition and during Ewing's tests. From these measurements, HRV parameters (using time and frequency domain analysis) were determined in 20 right MCA and 20 left MCA ischemic stroke patients, in the first 6 months after the acute event. Data were compared with 20 age- and sex-matched healthy controls. All the patients were right handed. In ischemic stroke patients, HRV parameters were significantly modified compared to controls (p < 0.05) and we found asymmetric responses to different stimulation autonomic tests between right and left hemisphere. Parameters illustrating the parasympathetic predominance in time domain (RMSSD) and frequency domain (HF) analysis were higher in left hemisphere stroke compared to right hemisphere stroke patients (p < 0.01) in resting state. From Ewing's battery test, patients with left hemisphere ischemic stroke showed predominance of parasympathetic activity to deep breathing (p < 0.01), while HRV parameters in right hemisphere ischemic stroke patients described a reduced cardiac parasympathetic innervation (p < 0.01). Cardiac autonomic imbalance occurs more often after right hemisphere ischemic stroke. HRV study may highlight cardiac dysfunctions that increase the risk of cardiovascular complications and portends a poor long-term outcome.
Conventional therapies do not provide paralyzed patients with closed-loop sensorimotor integration for motor rehabilitation. This work presents the recoveriX system, a hardware and software platform that combines a motor imagery (MI)-based brain-computer interface (BCI), functional electrical stimulation (FES), and visual feedback technologies for a complete sensorimotor closed-loop therapy system for poststroke rehabilitation. The proposed system was tested on two chronic stroke patients in a clinical environment. The patients were instructed to imagine the movement of either the left or right hand in random order. During these two MI tasks, two types of feedback were provided: a bar extending to the left or right side of a monitor as visual feedback and passive hand opening stimulated from FES as proprioceptive feedback. Both types of feedback relied on the BCI classification result achieved using common spatial patterns and a linear discriminant analysis classifier. After 10 sessions of recoveriX training, one patient partially regained control of wrist extension in her paretic wrist and the other patient increased the range of middle finger movement by 1 cm. A controlled group study is planned with a new version of the recoveriX system, which will have several improvements.
The purpose of this study was to evaluate the effects of mirror therapy program in addition with physical therapy methods on upper limb recovery in patients with subacute ischemic stroke. 15 subjects followed a comprehensive rehabilitative treatment, 8 subjects received only control therapy (CT) and 7 subjects received mirror therapy (MT) for 30 min every day, five times a week, for 6 weeks in addition to the conventional therapy. Brunnstrom stages, Fugl-Meyer Assessment (upper extremity), the Ashworth Scale, and Bhakta Test (finger flexion scale) were used to assess changes in upper limb motor recovery and motor function after intervention. After 6 weeks of treatment, patients in both groups showed significant improvements in the variables measured. Patients who received MT showed greater improvements compared to the CT group. The MT treatment results included: improvement of motor functions, manual skills and activities of daily living. The best results were obtained when the treatment was started soon after the stroke. MT is an easy and low-cost method to improve motor recovery of the upper limb.
The endocannabinoid system (ECS) dynamically regulates many aspects of mammalian physiology. ECS has gained substantial interest since growing evidence suggests that it also plays a major role in several pathophysiological conditions due to its ability to modulate various underlying mechanisms. Furthermore, cannabinoids, as components of the cannabinoid system (CS), have proven beneficial effects such as anti-inflammatory, immunomodulatory, neuromodulatory, antioxidative, and cardioprotective effects. In this comprehensive review, we aimed to describe the complex interaction between CS and most common age-related diseases such as neuro-degenerative, oncological, skeletal, and cardiovascular disorders, together with the potential of various cannabinoids to ameliorate the progression of these disorders. Since chronic inflammation is postulated as the pillar of all the above-mentioned medical conditions, we also discuss in this paper the potential of CS to ameliorate aging-associated immune system dysregulation.
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