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Biofeedback is used for regulating vestibular adaptation and balance by providing real-time stimulus to the individual during physical activities. This study aimed at (1) developing a wearable device, which tracks balance, counts the number and the direction of balance losses and provides haptic biofeedback through real-time vibration stimulus (2) investigating device efficacy on an adolescent medulloblastoma patient during static and dynamic tasks.

A 16-year-old medulloblastoma patient used the device during 10-m walking and single-leg stance tests. The knee joint kinematics and the number and direction of balance losses were recorded for “with” and “without” biofeedback conditions.

The device helped regulate the knee joint kinematics and reduce the number of balance losses of the medulloblastoma patient. The knee joint movement pattern similarity of the control subject was highly correlated (R² = 0.997, RMSE = 1.232). Conversely, medulloblastoma patient knee joint movement pattern similarity was relatively weak (R² = 0.359, RMSE = 18.6) when “with” and “without” biofeedback conditions were compared. The number of balance losses decreased when the medulloblastoma patient was guided with biofeedback.

The major limitation of this pilot study is the lack of a large and homogeneous number of participants. The medulloblastoma patient used the device while walking after she was given enough time to get used to the tactile biological feedback, so the long-term effect of the device and biofeedback guidance were not investigated. Additionally, the potential desensitization with prolonged use of the device was not evaluated.

Biofeedback reduced the number of balance losses; additionally, the knee joint movement pattern was regulated during static and dynamic tasks. This device can be integrated into the physical therapy of patients with balance, vestibular and postural control impairments.

This is compact and has an easy-to-wear design, patients, who have balance and postural control impairments, can practically use the device during their activities of daily living.

The device promotes physical activity adaptation and regulates gait through continuous and real-time balance control. Its design makes it simple for the user to wear it beneath clothing while using the sensor.

Training Officers, Personnel Officers, Welfare Officers, Instructors and line managers find that much of their time is being taken up with activities related to destocking and labour shedding. But as well as this they also find that their everyday activities and roles are changing too. Increasingly they find themselves taking a caring role with staff; assisting whenever possible with their health, general welfare and mental well‐being. They find themselves talking with staff about general problems of living in today's changing world; about avoiding illness; ways of coping with social and personal disruption in their lives; about maintenance of sound health — even about avoiding health‐denying habits. At first sight all this seems due to the increased general population awareness of health and well‐being — the impact of Health Education Council public campaigns for instance. But is it? Is this the only reason?

The study investigated the effects of two mental training strategies separately and combined on subjects’ shooting performance following an endurance march. Further, the study examined the suitability of a ten‐session training programme for the police force. On Trial 1, following a three hour march, 44 subjects shot 25 rounds. Subjects were then randomly assigned to four groups (biofeedback, relaxation, combined biofeedback and relaxation and control). After two weeks of mental training, subjects performed both tasks again on Trial 2. A repeated two‐way ANOVA indicated a significant improvement (p < 0.01) in shooting accuracy by the combined group. Suitability for this mental training programme was strongly supported by the experimental groups (71 per cent to 80 per cent). Subjects were generally better able to relax and focus. They were also more aware of their body and their physiological control. Results are discussed in light of potential benefits for cognitive strategies in precision tasks following endurance activities.

Mathematical models of biofeedback learning provide empirical laws of these processes and could be used in order to improve experiments. The systemic approach provides a well‐adapted framework, in which learning is studied as a control problem. The model proposed here is a system of recurrence equations involving the successive measurements of the subject's physiological activity collected by the biofeedback device, and also the performance index presented to the subject. A parameter identification method is described and tested on a computer simulated process.

One of the main causes of long-term prosthetic abandonment is the lack of ownership over the prosthesis, which was caused mainly by the absence of sensory information regarding the lost limb. The period where the patient learns how to interact with a prosthetic device is critical in rehabilitation. This ideally happens within the first months after amputation, which is also a period associated with the consolidation of brain changes. Different studies have shown that the introduction of feedback mechanisms can be crucial to bypass the lack of sensorial information. To develop a biofeedback system for the rehabilitation of transfemoral amputees – controlled via electromyographic (EMG) activity from the leg muscles – that can provide real-time visual and/or vibratory feedback for the user.

The system uses surface EMG to control two feedback mechanisms, which are the knee joint of a prosthetic leg of a humanoid avatar in a virtual reality (VR) environment (visual feedback) and a matrix of 16 vibrotactile actuators placed in the back of the user (vibratory feedback). Data acquisition was inside a Faraday Cage using an OpenEphys® acquisition board for the surface EMG recordings. The tasks were performed on able-bodied participants, with no amputation, and for this, the dominant leg of the user was immobilized using an orthopedic boot fixed on the chair, allowing only isometric contractions of target muscles, according to the Surface EMG for Non-Invasive Assessment of Muscles (SENIAM) standard. The authors test the effectiveness of combining vibratory and visual feedback and how task difficulty affects overall performance.

The authors' results show no negative interference combining both feedback modalities and that performance peaked at the intermediate difficulty. These results provide powerful insights of what can be accomplished with the population of amputee people. By using this biofeedback system, the authors expect to engage another sensory modality in the process of spatial representation of a virtual leg, bypassing the lack of information associated with the disruption of afferent pathways following amputation.

The authors developed a showcase with a new protocol and feedback mechanisms showing the protocol's safety, efficiency and reliability. However, since this system is designed for patients with leg amputation, the full extent of the effects of the biofeedback training can only be assessed after the evaluation with the amputees, and the results obtained so far establish a safe and operational protocol to accomplish this.

In this study, the authors proposed a new biofeedback device intended to be used in the preprosthetic rehabilitation phase for people with transfemoral amputation. With this new system, the authors propose a mechanism to bypass the lack of sensory information from a virtual prosthesis and help to assimilate visual and vibrotactile stimuli as a cue for movement representation.

With this new system, the authors propose a mechanism to bypass the lack of sensory information from a virtual prosthesis and help to assimilate visual and vibrotactile stimuli as a cue for movement representation.

The authors' results show that all users were capable of recognizing both feedback modalities, both separate and combined, being able to respond accordingly throughout the tasks. The authors also show that for a one-session protocol, the last difficulty level imposed a greater challenge for most users, explained by the significant drop in performance disregarding the feedback modality. Lastly, the authors believe this paradigm can provide a better process for the embodiment of prosthetic devices, fulfilling the lack of sensory information for the users.

The purpose of this paper was to investigate the response of good and poor sleepers toward audio-visual stimulation via prefrontal theta EEG measurement.

The experiment included ten healthy subjects that were chosen after going through the Pittsburgh Sleep Quality Index (PSQI). They were divided into two groups that include five good and five poor sleepers. Next, in order to clarify the effects of audio-visual biofeedback during daytime, each subject was asked to go through six two-minute tasks that include: pre-baseline, eyes open at rest, eyes closed at rest, audio biofeedback with eyes open, video biofeedback also with eyes open, and post-baseline.

In Task 4, the audio stimulation task, both types of sleepers elicited higher theta waves due to demand in mental activity and also a meditation state. It was significantly higher in poor sleeper that demonstrated a peak difference of 25 percent compared to its good sleeper counterpart. In Task 5, the visual stimulation task, through the use of random numbers having blue and red color background, the theta amplitudes of good and poor sleepers drop together, due to beta waves becoming dominant, as the task required attention and focussed accounting for reduced theta amplitudes. The study was able to prove the use of prefrontal EEG in measuring and evaluating sleep quality by examining theta variation.

This paper proposed a novel and convenient method for evaluating sleep quality by utilizing only a single channel prefrontal EEG measurement.

The idea is to exploit the natural stability and performance of the human arm during movement, execution and manipulation. The purpose of this paper is to remotely control a handling robot with a low cost but effective solution.

The developed approach is based on three different techniques to be able to ensure movement and pattern recognition of the operator’s arm as well as an effective control of the object manipulation task. In the first, the methodology works on the kinect-based gesture recognition of the operator’s arm. However, using only the vision-based approach for hand posture recognition cannot be the suitable solution mainly when the hand is occluded in such situations. The proposed approach supports the vision-based system by an electromyography (EMG)-based biofeedback system for posture recognition. Moreover, the novel approach appends to the vision system-based gesture control and the EMG-based posture recognition a force feedback to inform operator of the real grasping state.

The main finding is to have a robust method able to gesture-based control a robot manipulator during movement, manipulation and grasp. The proposed approach uses a real-time gesture control technique based on a kinect camera that can provide the exact position of each joint of the operator’s arm. The developed solution integrates also an EMG biofeedback and a force feedback in its control loop. In addition, the authors propose a high-friendly human-machine-interface (HMI) which allows user to control in real time a robotic arm. Robust trajectory tracking challenge has been solved by the implementation of the sliding mode controller. A fuzzy logic controller has been implemented to manage the grasping task based on the EMG signal. Experimental results have shown a high efficiency of the proposed approach.

There are some constraints when applying the proposed method, such as the sensibility of the desired trajectory generated by the human arm even in case of random and unwanted movements. This can damage the manipulated object during the teleoperation process. In this case, such operator skills are highly required.

The developed control approach can be used in all applications, which require real-time human robot cooperation.

The main advantage of the developed approach is that it benefits at the same time of three various techniques: EMG biofeedback, vision-based system and haptic feedback. In such situation, using only vision-based approaches mainly for the hand postures recognition is not effective. Therefore, the recognition should be based on the biofeedback naturally generated by the muscles responsible of each posture. Moreover, the use of force sensor in closed-loop control scheme without operator intervention is ineffective in the special cases in which the manipulated objects vary in a wide range with different metallic characteristics. Therefore, the use of human-in-the-loop technique can imitate the natural human postures in the grasping task.

With the increased interest in work‐related stress that has evolved in the last several years has come a corresponding interest in stress management techniques and interventions. The effectiveness of four individual stress management techniques (relaxation training, biofeedback, cognitive techniques, and exercise) are considered and some of the weaknesses of much of the current stress management evaluation research are identified. Finally, some suggestions are made for improving the overall quality of such research.