Abstract
Current state-of-the-art quantitative assessments of abnormal neuro-mechanics (e.g., spasticity, rigidity, dystonia) require sophisticated measurement systems that, together with the lengthiness of the data acquisition, make these approaches impractical for the clinical setting. Our long-term goal is to create a tool that enhances the capability of therapists to diagnose abnormal neuro-mechanics without the need of lengthy procedures and sophisticated equipment. Towards this direction, we present a haptic display of abnormal limb neuro-mechanics. This haptic display can be used as a training device for clinicians to understand the causality of the haptic sensation associated with neurological impairments and abnormal biomechanics during manipulation of a patients' limb. Other uses include the testing of operational research algorithms to maximize the exchange of haptic information, reproducing conditions of human-human interaction, and a test bed for developing novel assessment techniques and targeted interventions. Experimental results support the hypothesis that the best assessment of abnormalities can be obtained via specific manipulation strategies.
Highlights
IntroductionA common consequence of many neurological disorders like cerebral palsy, Parkinson's disease, or stroke (to name a few) is the appearance of atypical neuro-mechanical conditions such as an increase in muscle tone (hypertonia) due to active contraction of the muscle, hyperexcitability of motoneurons causing excessive co-activation, muscle contractures, etc
A common consequence of many neurological disorders like cerebral palsy, Parkinson's disease, or stroke is the appearance of atypical neuro-mechanical conditions such as an increase in muscle tone due to active contraction of the muscle, hyperexcitability of motoneurons causing excessive co-activation, muscle contractures, etc
Other experiments In addition to this experiment, we are currently using this haptic display to i) assess the capabilities of naïve subjects and expert therapists to correctly identify the nature and severity of hypertonic impairments and to ii) assess how the perception of hypertonia is affected by the impedance introduced by the virtual connection between a patient and a clinician interacting remotely [35]
Summary
A common consequence of many neurological disorders like cerebral palsy, Parkinson's disease, or stroke (to name a few) is the appearance of atypical neuro-mechanical conditions such as an increase in muscle tone (hypertonia) due to active contraction of the muscle, hyperexcitability of motoneurons causing excessive co-activation, muscle contractures, etc. It is common in today's clinical practice to manipulate the patient's limbs to diagnose these abnormal neuro-mechanical changes Through such physical interaction, clinicians extract as much information as possible to infer the patients' condition, such as in the assessment of hypertonic conditions [1,2,3] (e.g., spasticity, rigidity, dystonia, among others). Clinicians extract as much information as possible to infer the patients' condition, such as in the assessment of hypertonic conditions [1,2,3] (e.g., spasticity, rigidity, dystonia, among others) This approach is subjective [4], which may be a limitation when inferring the nature and gravity of the impairment since the effect generated by pluri-articular muscles to multi-joint mechanics can be misjudged. Some of the most important clinical problems have been ignored in these engineering approaches
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