Objective-The current study evaluates the efficacy of a P300-based Brain-Computer Interface (BCI) communication device for individuals with advanced ALS.Methods-Participants attended to one cell of a N×N matrix while the N rows and N columns flashed randomly. Each cell of the matrix contained one character. Every flash of an attended character served as a rare event in an oddball sequence and elicited a P300 response. Classification coefficients derived using a stepwise linear discriminant function were applied to the data after each set of flashes. The character receiving the highest discriminant score was presented as feedback.Results-In Phase I, six participants used a 6×6 matrix on 12 separate days with a mean rate of 1.2 selections/min and mean online and offline accuracies of 62% and 82% respectively. In Phase II, four participants used either a 6×6 or a 7×7 matrix to produce novel and spontaneous statements with a mean online rate of 2.1 selections/min and online accuracy of 79%. The amplitude and latency of the P300 remained stable over 40 weeks.Conclusions-Participants could communicate with the P300-based BCI and performance was stable over many months.Significance-BCIs could provide an alternative communication and control technology in the in daily lives of people severely disabled by ALS.

The rehabilitation of patients should not only be limited to the first phases during intense hospital care but also support and therapy should be guaranteed in later stages, especially during daily life activities if the patient’s state requires this. However, aid should only be given to the patient if needed and as much as it is required. To allow this, automatic self-initiated movement support and patient-cooperative control strategies have to be developed and integrated into assistive systems. In this work, we first give an overview of different kinds of neuromuscular diseases, review different forms of therapy, and explain possible fields of rehabilitation and benefits of robotic aided rehabilitation. Next, the mechanical design and control scheme of an upper limb orthosis for rehabilitation are presented. Two control models for the orthosis are explained which compute the triggering function and the level of assistance provided by the device. As input to the model fused sensor data from the orthosis and physiology data in terms of electromyography (EMG) signals are used.

Patients with completely locked-in syndrome are conscious and alert, even though they have lost the ability to control their muscles. 1 These patients require a communication channel independent of the motor system. EEG-based brain-computer interfaces (BCIs) are an available communication aid, but aside from the intensive training that most of them demand, not all patients achieve proficiency in EEG control. Here we report an alternative method to re-establish communication in a 46-year-old woman with ALS. At the time of the study, she had been diagnosed with ALS for more than 5 years and had been artificially ventilated and fed for 3 years. For 12 months before this study, she was completely locked in, showing no signs of voluntary motor control including eye movements (measured with electro-oculogram) and external sphincter activity (measured with an anal electromyography electrode). Before entering the locked-in state, the patient requested continuation of life support from her family. The family insisted on respecting the patient's will beyond the locked-in state. EEG responses derived from auditory event-related paradigms indicated preserved cognitive functions, 2 which, together with the experiment described below, excludes persistent vegetative state. Prior to this experiment, the patient participated in BCI training as described elsewhere, 3 which was terminated after 6 months without success. Because of this failure, we hypothesized that subdural electrode placement and recording, which offer greater signal-to-noise-ratio than scalp EEG recordings, would provide a greater chance of BCI communication. After consultation with the ethics committee and the patient's husband, we elected to pursue this. To reinstate communication and to obtain informed consent, we tested a new means of communication based on manipulation of the salivary pH. Salivary flow can be elicited by imagery of food. 4,5 As flow rate increases upon stimulation, the concentration of bicarbonate increases, resulting in an increase in salivary pH. 6 First, we determined whether the patient was capable of manipulating the salivary pH by food imagery. Three sessions with 10 trials each were performed. Each trial consisted of a 2-minute rest period to establish a baseline and a response period lasting 2 minutes. The pH was measured by a digital pH meter (GPRT-1400-AN; Greisinger Electronic GmbH, Germany). The pH electrode was placed in the oral cavity. After each trial, the saliva was removed from the patient's mouth. During the test period, the patient was required to imagine the taste of either lemon or milk. A nonrandomized order (five trials of lemon imagery followed by five trials of milk imagery, and vice versa) was chosen to determine consistent pH responses upon repeated imagery of the same stimulus. There was a difference between pH of nonstimulated baseline saliva and pH of stimulated saliva for both imagery conditions (p Ͻ 0.001); mean pH increased during lemon imagery and decreased during milk imagery (figure, A, task A). Next, t...

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The goal of this work is the development and performance analysis of control algorithms for new soft fluidic actuators with rotary elastic chambers (REC-actuators). Due to their inherent compliancy these actuators fulfill the requisites for building intrinsically safe mechanisms as assistance robots and motion therapy devices, working in direct physical contact with humans. Besides the difficulties common for control design of pneumatic systems, these actuators itself posses several nonlinear characteristics causing specific problems in their modeling and control. In this work the decentralized joint control scheme is implemented, where the position controller has a cascade structure with a non-linear model based pressure control in the inner loop. Two different position control approaches, which require minimal information on the dynamics of the actuator mechanical subsystem, were investigated and tested: sliding mode control with time delay estimation as well as a fuzzy control with parameter optimization based on genetic algorithms.