ABSTRACT
The loss of sensitivity of the upper limb due to central or peripheral neurological injuries severely limits the ability to manipulate objects, hindering personal independence. Non-invasive augmented sensory feedback techniques are used to promote neural plasticity hence to restore the grasping function. We devised a wearable device for hand sensorimotor rehabilitation capable of reliably detect transient tactile events based on custom piezoelectric polyvinylidene fluoride (PVDF) sensors and deliver discrete bursts of vibrations upon these events. We integrated the sensors into a fabric glove and tested the device in a pilot bench test exploring its ability to detect object contact and release as well as object slippage. Due to their broad bandwidth, the sensors proved to be suitable for both the applications: they responded with clear peaks when touching or releasing the object and increased the high-frequency content of the signal during slippage.
Subject(s)
Feedback, Sensory , Wearable Electronic Devices , Humans , Hand , Upper Extremity , TouchABSTRACT
Electromyographic (EMG) recordings of muscle activity using monopolar electrodes suffer from poor spatial resolution due to the crosstalk from neighbouring muscles. This effect has mainly been studied on surface EMG recordings. Here, we use Principal Component Analysis (PCA) to reduce the crosstalk in recordings from unipolar epimysial electrodes implanted in three transhumeral amputees. We show that the PCA-transformed signals have, on average, a better signal-tonoise ratio than the original unipolar recordings. Preliminary investigations show that this transformation is stable over long periods of time. If the latter is confirmed, our results show that the combination of PCA with unipolar electrodes allows for a higher number of muscles to be targeted in an implant (compared with bipolar electrodes), thus facilitating 1-to-1 proportional control of prosthetic hands.
