The Haptic Bracelets: Gait rehabilitation after Stroke

Restoring mobility and rehabilitation of gait are high priorities for rehabilitation of neurological conditions. Cueing using metronomic rhythmic sensory stimulation has been shown to improve gait, but most versions of this approach have used auditory and visual cues. In contrast, we propose the development of a prototype wearable system for rhythmic cueing based on haptics. The main aim of this research is to investigate how real-time gait monitoring and rhythmic haptic cueing can assist with gait rehabilitation for neurological conditions

Rhythmic Micro-Gestures: Discreet Interaction On-the-Go

We present rhythmic micro-gestures, micro-movements of the hand that are repeated in time with a rhythm. We present a user study that investigated how well users can perform rhythmic micro-gestures and if they can use them eyes-free with non-visual feedback. We found that users could successfully use our interaction technique (97% success rate across all gestures) with short interaction times, rating them as low difficulty as well. Simple audio cues that only convey the rhythm outperformed animations showing the hand movements, supporting rhythmic micro-gestures as an eyes-free input technique

An Analysis of Rhythmic Staccato-Vocalization Based on Frequency Demodulation for Laughter Detection in Conversational Meetings

Human laugh is able to convey various kinds of meanings in human communications. There exists various kinds of human laugh signal, for example: vocalized laugh and non vocalized laugh. Following the theories of psychology, among all the vocalized laugh type, rhythmic staccato-vocalization significantly evokes the positive responses in the interactions. In this paper we attempt to exploit this observation to detect human laugh occurrences, i.e., the laughter, in multiparty conversations from the AMI meeting corpus. First, we separate the high energy frames from speech, leaving out the low energy frames through power spectral density estimation. We borrow the algorithm of rhythm detection from the area of music analysis to use that on the high energy frames. Finally, we detect rhythmic laugh frames, analyzing the candidate rhythmic frames using statistics. This novel approach for detection of `positive' rhythmic human laughter performs better than the standard laughter classification baseline.Comment: 5 pages, 1 figure, conference pape

The locust frontal ganglion: a central pattern generator network controlling foregut rhythmic motor patterns

The frontal ganglion (FG) is part of the insect stomatogastric nervous system and is found in most insect orders. Previous work has shown that in the desert locust, Schistocerca gregaria, the FG constitutes a major source of innervation to the foregut. In an in vitro preparation, isolated from all descending and sensory inputs, the FG spontaneously generated rhythmic multi-unit bursts of action potentials that could be recorded from all its efferent nerves. The consistent endogenous FG rhythmic pattern indicates the presence of a central pattern generator network. We found the appearance of in vitro rhythmic activity to be strongly correlated with the physiological state of the donor locust. A robust pattern emerged only after a period of saline superfusion, if the locust had a very full foregut and crop, or if the animal was close to ecdysis. Accordingly, haemolymph collected at these stages inhibited an ongoing rhythmic pattern when applied onto the ganglion. We present this novel central pattern generating system as a basis for future work on the neural network characterisation and its role in generating and controlling behaviour

Steady-State movement related potentials for brain–computer interfacing

An approach for brain-computer interfacing (BCI) by analysis of steady-state movement related potentials (ssMRPs) produced during rhythmic finger movements is proposed in this paper. The neurological background of ssMRPs is briefly reviewed. Averaged ssMRPs represent the development of a lateralized rhythmic potential, and the energy of the EEG signals at the finger tapping frequency can be used for single-trial ssMRP classification. The proposed ssMRP-based BCI approach is tested using the classic Fisher's linear discriminant classifier. Moreover, the influence of the current source density transform on the performance of BCI system is investigated. The averaged correct classification rates (CCRs) as well as averaged information transfer rates (ITRs) for different sliding time windows are reported. Reliable single-trial classification rates of 88%-100% accuracy are achievable at relatively high ITRs. Furthermore, we have been able to achieve CCRs of up to 93% in classification of the ssMRPs recorded during imagined rhythmic finger movements. The merit of this approach is in the application of rhythmic cues for BCI, the relatively simple recording setup, and straightforward computations that make the real-time implementations plausible

Identification of a rhythmic firing pattern in the enteric nervous system that generates rhythmic electrical activity in smooth muscle

The enteric nervous system (ENS) contains millions of neurons essential for organization of motor behavior of the intestine. It is well established that the large intestine requires ENS activity to drive propulsive motor behaviors. However, the firing pattern of the ENS underlying propagating neurogenic contractions of the large intestine remains unknown. To identify this, we used high-resolution neuronal imaging with electrophysiology from neighboring smooth muscle. Myoelectric activity underlying propagating neurogenic contractions along murine large intestine [also referred to as colonic migrating motor complexes, (CMMCs)] consisted of prolonged bursts of rhythmic depolarizations at a frequency of ∼2 Hz. Temporal coordination of this activity in the smooth muscle over large spatial fields (∼7 mm, longitudinally) was dependent on the ENS. During quiescent periods between neurogenic contractions, recordings from large populations of enteric neurons, in mice of either sex, revealed ongoing activity. The onset of neurogenic contractions was characterized by the emergence of temporally synchronized activity across large populations of excitatory and inhibitory neurons. This neuronal firing pattern was rhythmic and temporally synchronized across large numbers of ganglia at ∼2 Hz. ENS activation preceded smooth muscle depolarization, indicating rhythmic depolarizations in smooth muscle were controlled by firing of enteric neurons. The cyclical emergence of temporally coordinated firing of large populations of enteric neurons represents a unique neural motor pattern outside the CNS. This is the first direct observation of rhythmic firing in the ENS underlying rhythmic electrical depolarizations in smooth muscle. The pattern of neuronal activity we identified underlies the generation of CMMCs