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Horse rider ability has long been measured using horse performance, competition results and visual observation. Scientific methods of measuring rider ability on the flat are emerging such as measuring position angles and harmony of the horse-rider system. To date no research has quantified rider ability in show jumping. Kinematic analysis and motion sensors have been used in sports other than show...
We present a device for recording and analyzing upper limb movements and muscle activities in a single unit. The device's outputs are related to aspects of clinical assessment such as joint coordination, fatigue and muscle synergies. A comparison with an optoelectronic motion capture system was also carried out during a hand to mouth and a hand to contralateral shoulder task. High correlation was...
The current work describes a methodology to automatically detect the severity of bradykinesia in motor disease patients using wireless, wearable accelerometers. This methodology was tested with cross validation through a sample of 20 Parkinson's disease patients. The assessment of methodology was carried out through some daily living activities which were detected using an activity recognition algorithm...
Disrupted sleep patterns are a significant problem in the elderly, leading to increased cognitive dysfunction and risk of nursing home placement. A cost-effective and unobtrusive way to remotely monitor changing sleep patterns over time would enable improved management of this important health problem. We have developed an algorithm to derive sleep parameters such as bed time, rise time, sleep latency,...
The study and measurement of grasping actions and forces in humans is important in a variety of contexts. In infants, it can give insights on the typical and atypical motor development, while it poses functional and operative requirements that are not fully matched by current sensing technology. Novel approaches for measuring infants' grasping actions are based on sensorized platform usable in natural...
One of the areas of great demand for the need of continuous monitoring, patient participation and medical prediction is that of mood disorders, more specifically bipolar disorders. Due to the unpredictable and episodic nature of bipolar disorder, it is necessary to take the traditional standard procedures of mood assessment through the administration of rating scales and questionnaires and integrate...
Recently, there has been an increasing interest in upper-limb prosthetic hand control, but most of these studies focus on the detection of exact motion intentions. Therefore, the responses to unexpected disturbance are not taken into consideration. On the other hand, unimpaired people respond to external disturbances by reflexive responses, hence, it is important to explore how this kind of reactive...
We investigated the performance of a new sparse neuroimaging method, i.e., Variation-Based Sparse Cortical Current Density (VB-SCCD) using magnetoencephalography (MEG) data to reconstruct extended cortical sources and their spatial distributions on the cortical surface. We conducted Monte Carlo simulation studies to compare the performance of the VB-SCCD method with different number of cortical sources...
Following hand function impairment caused by a neurological disorder, the functional level of the upper extremities has to be assessed in the clinical and rehabilitation settings. Current hand function evaluation tests are somewhat imprecise. Instrumented gloves allow finger motion monitoring during the performance of skilled tasks, such as grasping objects. As a result, they provide an objective...
In this paper, an algorithm able to detect epilepsy seizure based on 3D accelerometers and with patient adaptation is presented. This algorithm is based on a Bayesian approach using hidden Markov models for statistical modelling of moves signals. A particular focus is set on the learning procedure and in particular on its initialisation to ensure a good learning and to avoid numerical instability...
This paper describes an effort to estimate variations in cognitive effort among cancer survivors experiencing treatment related cognitive decline. EEG-based cognitive state sensing algorithms were validated in the context of an experiment with 5 brain cancer and 5 breast cancer survivors. Workload was manipulated by varying text complexity and time pressure. Analysis indicates that EEG-based cognitive...
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