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Background: Anxiety is one of the most common mental disorders among school-going children and adolescents worldwide. Multiple factors like internalization of the symptoms, lack of proper objective assessment, societal stigmatization, and influence of parental pressure may alter the prevalence and incidence. Aim: The current study is done to identify the prevalence of anxiety disorders in school children and their associated risk factors. Method: A total of 550 students (266 boys and 284 girls), studying in grades 8 to 12 in urban and rural schools chosen by stratified random sampling, were subjected to a questionnaire survey by the team of trained investigators using “Screen for Child Anxiety and Emotion-related Disorder (SCARED)—child Version.” Results: Total prevalence of anxiety assessed using the SCARED scale was 51%. The prevalence of subtypes of anxiety disorders was also identified viz, generalized anxiety disorder—16%, panic disorder—23%, school phobia—17%, separation anxiety—31%, and social phobia—13%. All the disorders showed higher incidence in girls ( P < .01). Discussion: The anxiety disorders were associated significantly with students from rural schools, those studying in the Tamil medium, those staying in hostels, students who had mothers who were employed, and living in extended family environments. Students who walked to school and who had neither of their parents as caregivers were more likely to have panic disorder, school phobia, social phobia, and separation anxiety disorder. Conclusion: This study documented a higher prevalence of anxiety disorders and subtypes and highlighted the factors associated with anxiety disorders in school students of the adolescent age group.

A novel synthetic strategy for the construction of substituted imidazoles from acetophenones and benzylamines via N-heterocyclic carbene (NHC) - catalysis was reported. This reaction can be performed under solvent-free condition without pre-functionalization of substrates. Various substituted acetophenones and benzylamines were converted to its corresponding imidazoles with good to excellent yields.

You probably believe that a latent relationship between the brain and lower limbs exists and it varies across different walking conditions (e.g., walking with or without an exoskeleton). Have you ever thought what the distributions of measured signals are? To address this question, we simultaneously collected electroencephalogram (EEG) and electromyogram (EMG) signals while healthy participants were conducting four overground walking conditions without any constraints (e.g., specific speed). The EEG results demonstrated that a wide range of frequencies from delta band to gamma band were involved in walking. The EEG power spectral density (PSD) was significantly different in sensorimotor and posterior parietal areas between exoskeleton-assisted walking and non-exoskeleton walking. The EMG PSD difference was predominantly observed in the theta band and the gastrocnemius lateralis muscle. EEG-EMG PSD correlations differed among walking conditions. The alpha and beta bands were primarily involved in consistently increasing EEG-EMG PSD correlations across the walking conditions, while the theta band was primarily involved in consistently decreasing correlations as observed in the EEG involvement. However, there is no dominant frequency band as observed in the EMG involvement. Channels located over the sensorimotor area were primarily involved in consistently decreasing EEG-EMG PSD correlations and the outer-ring channels were involved in the increasing EEG-EMG PSD correlations. Our study revealed the spectral and spatial distributions relevant to overground walking and deepened the understanding of EEG and EMG representations during locomotion, which may inform the development of a more human-compatible exoskeleton and its usage in motor rehabilitation.

Gait disorders in neurologically disabled people can be treated by various techniques available today which include passive orthoses, functional electrical stimulation (FES) and robot assisted gait training devices (RAGT). However, each system has its own drawback. For example, gait rehabilitation with orthosis is physically taxing for the patient with no significant functional improvement. FES uses muscle powers as physiological actuators to promote balance and improve gait but leads to fatigue, along with poor control of joint trajectories. RAGT devices including powered exoskeletons, gait rehabilitation systems employing programmable footplates and mobile training platforms, have shown significant advantages but the devices are not yet mature due to numerous drawbacks associated with physical and cognitive interaction, energy-management and portability issues. The combination of FES technology and RAGT devices, often named hybrid FES–robot technologies, has arisen as a promising approach to aid in gait restoration. This work reports a comprehensive review on the hybrid FES–robot technologies over the last decades, focusing on different mechanical structures, actuator designs, sensing technologies, and control approaches. The hybrid robotic structures are classified into two categories: (i) orthotic-based hybrid systems, where (a) FES is used to stimulate the muscles and produce joint torque while the robotic system acts as energy dissipating device, and (b) FES and robotic systems are both torque-generating devices; and (ii) non-orthotic based hybrid systems. The review compiles a variety of sources and illustrates the technology’s most important challenges in the fields of hybrid rehabilitation robotics which may contribute towards further development of hybrid robot systems.

For the development of protocols pertaining to highly specialized rehabilitation, it is vital to understand how specific exercises and rehabilitation robotic treatments influence locomotor adaptation. Therefore, experimental results are necessary to understand how these adaptive mechanisms depend on the role of shared training variables for optimizing the rehabilitation outcomes. In this study, we aimed to assess the combined effects of active body weight support (BWS) and robot-applied resistance/assistance training on the muscle function during robotic-assisted treadmill walking. Altogether, ten healthy participants enrolled in this study. Participants were asked to walk with different percentages levels of BWS (0%, 15% and 30% of the participants' body weight) and robot-applied resistance/assistance force (0%, 5% and 10% of the participants' body weight). Temporal gait parameters and muscular activity from gait related muscles were recorded. Overall, the provision of BWS increased the activity in muscles related to pelvic stability (i.e., Biceps Femoris) and reduced muscular activity associated with weight loading and foot clearance (i.e., Rectus Femoris and Tibialis Anterior). Moreover, resistance training did not show any superiority over assistance training in activating gait related muscles in healthy subjects, although different motor adaptations may be involved. Keywords— Body weight support, Gait, Muscle weakness, Rehabilitation robotics, Robot-assisted gait training, Robotic assistance/resistance training.

Since manual rehabilitation therapy can be taxing for both the patient and the physiotherapist, a gait rehabilitation robot has been built to reduce the physical strain and increase the efficacy of the rehabilitation therapy. The prototype of the gait rehabilitation robot is designed to provide assistance while walking for patients with abnormal gait pattern and it can also be used for rehabilitation therapy to restore an individual's normal gait pattern by aiding motor recovery. The Gait Rehabilitation Robot uses gait event based synchronization, which enables the exoskeleton to provide synchronous assistance during walking that aims to reduce the lower-limb muscle activation. This study emphasizes on the biomechanical effects of assisted walking on the lower limb by analyzing the EMG signal, knee joint kinematics data that was collected from the right leg during the various experimental conditions. The analysis of the measured data shows an improved knee joint trajectory and reduction in muscle activity with assistance. The result of this study does not only assess the functionality of the exoskeleton but also provides a profound understanding of the human-robot interaction by studying the effects of assistance on the lower limb.

Restoring normal walking abilities following the loss of them is a challenge. Importantly, there is a growing need for a better understanding of brain plasticity and the neural involvements for the initiation and control of these abilities so as to develop better rehabilitation programmes and external support devices. In this paper, we attempt to identify gait-related neural activities by decoding neural signals obtained from electroencephalography (EEG) measurements while subjects performed three types of walking: without exoskeleton (free walking), and with exoskeleton support (zero force and assisting force). An average classification accuracy of 92.0% for training and 73.8% for testing sets was achieved using features extracted from mu and beta frequency bands. Furthermore, we found that mu band features contributed significantly to the classification accuracy and were localized mainly in sensorimotor regions that are associated with the control of the exoskeleton. These findings contribute meaningful insight on the neural dynamics associated with lower limb movements and provide useful information for future developments of orthotic devices and rehabilitation programs.

Disability of lower limb affects voluntary movements and results in a low quality of life. Although people with disabled lower limb can restore their movements through assistive devices like wheelchair, such manner is not as natural as that healthy people perform locomotion. It would be better to regain movements by restoring the function of lower limb itself. Hence, an orthosis that can be worn on the disable lower limb might be a good choice. In addition, it is of interest to explore brain activities during walking with and without an orthosis. In this paper, we introduced a robotic knee exoskeleton that can provide assistive torque to facilitate walking. Three different conditions were employed here, namely free walking (FW, without exoskeleton), zero force (ZF, with the exoskeleton but no torque was provided), and assistive force (AF, torque was provided by the exoskeleton). During the walking, electrophysiological signals were simultaneously recorded. Partial directed coherence (PDC) was employed to measure connectivity strengths between channels and the obtained effective connectivity network was quantitatively assessed through a standard graph theoretical analysis framework. We found that the clustering coefficient was significantly increased when assistive torque was provided by the exoskeleton compared with FW and ZF. A decrease in path length was also found when assistive torque was provided. Our findings demonstrated that topological patterns of brain activities were distinctly different when people received assistive torque during walking. This study could be of meaningful significance on further orthosis development from the perspective of brain electrophysiological activity and insight into the understanding for brain plasticity and neural rehabilitation.