This paper describes a new treatment for essential tremor. A wearable orthosis, which can be adapted to each configuration of each joint of the upper limb, is able to apply effective dynamic force between consecutive segments of the upper limb and change its biomechanical characteristics. The orthosis is controlled by a computer with a dedicated software application that distinguishes between real time tremor and voluntary movement. The wearable orthosis is able to detect position, rate and acceleration of rotation of the joint by means of a chip gyroscope. This technology was evaluated in six patients suffering from essential tremor. The technique is non invasive and represents an alternative to medication and deep brain stimulation.
We describe a wearable orthosis and an associated algorithm for the simultaneous assessment and treatment of essential tremor, one of the most common movement disorders in humans involving an overactivity of the olivo-cerebellar pathways. A motor providing effective viscosity is fixed on a wearable orthosis in the upper limbs. The motor is controlled by a personal computer with software processing in real time the position and rate of rotation of the joint detected by a chip gyroscope. The orthosis can be used in a monitoring mode and in an active mode. The range of tremor suppression of the signals above the orthosis operational limit ranges from about 3% (percentile 5) to about 79% (percentile 95) in relation to energy in the monitoring mode. Considering both postural and kinetic, the mean tremor energy decreased from 55.49 +/- 22.93 rad2 s(-3) in the monitoring mode to 15.66 +/- 7.29 rad2 s(-3) in the active mode. Medians of power reduction were below 60% for the wrist and the elbow. In addition to supplying new information on the interactions between kinematics, dynamics and tremor genesis, this non-invasive technique is an alternative to current therapies. This new approach will provide new insights into the understanding of motor control.
The effect of walking velocity on force platform measures is examined by means of functional regression and nonfunctional regression analyses. The two techniques are compared using a data set of ground reaction forces. Functional data analysis avoids the need to identify significant points, and provides more information along the waveform.
This paper analyzes positive and negative motor signs in people with cerebral palsy (CP). Positive motor signs are those that lead to involuntarily increased frequency or magnitude of muscle activity. Negative motor signs describe insufficient muscle activity or insufficient control of muscle activity. This work present the use of a head mounted interface based on inertial technology to assess motor signs in fourteen users with CP. The task performance is related to the impairment. The analysis of the frequency shows that positive motor signs do not appear. However, users have limitations to maintain posture meaning that they have poor motor control, which is related to negative motor signs. The results and conclusions of this paper are considered a description of user's needs, which will be used to design and optimize a new human computer interface specifically designed for people with CP.
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