Sensorineural hearing loss is one of the most common chronic clinical disorders that we can easily encounter. The etiology of sensorineural hearing loss is multifactorial: congenital, idiopathic, traumatic, noise-induced, head injury induced, infectious disease, drug induced, degenerative, immune disorder, vestibular schwannoma and Meniere's disease. Many people are living with the discomfort of hearing loss because fundamental treatment is has not yet been found. Also due to the progress of medical science, human life span has been extended. As the result, the number of patients suffering from hearing loss has increased. But the present situation does not measure up to the demand for recovery of hearing loss. Hearing loss has a great influence on the quality of life. To overcome this situation, neural prostheses such as the cochlear implant and auditory brainstem implant are helpful for the rehabilitation of total deaf patients. Recently, due to the advancement of studies related to hair cell regeneration and the field of gene therapy on the inner ear has made big progress during the last few years. The purpose of this study is to describe the latest known causes and rehabilitation of sensorineural hearing loss.
Auditory Brain Stem Implants ; Cochlear Implants ; Communicable Diseases ; Correction of Hearing Impairment ; Craniocerebral Trauma ; Ear, Inner ; Genetic Therapy ; Hair ; Hearing Loss ; Hearing Loss, Sensorineural* ; Hearing* ; Humans ; Immune System Diseases ; Meniere Disease ; Neural Prostheses ; Neuroma, Acoustic ; Quality of Life ; Regeneration ; Rehabilitation*

A brain-machine interface (BMI) has recently been introduced to research a reliable control of machine from the brain information processing through single neural spikes in motor brain areas for paralyzed individuals. Small, wireless, and implantable BMI system should be developed to decode movement information for classifications of neural activities in the brain. In this paper, we have developed a totally implantable wireless neural signal transmission system (TiWiNets) combined with advanced digital signal processing capable of implementing a high performance BMI system. It consisted of a preamplifier with only 2 operational amplifiers (op-amps) for each channel, wireless bluetooth module (BM), a Labview-based monitor program, and 16 bit-RISC microcontroller. Digital finite impulse response (FIR) band-pass filter based on windowed sinc method was designed to transmit neural signals corresponding to the frequency range of 400 Hz to 1.5 kHz via wireless BM, measuring over -48 dB attenuated in the other frequencies. Less than +/-2% error by inputting a sine wave at pass-band frequencies for FIR algorithm test was obtained between simulated and measured FIR results. Because of the powerful digital FIR design, the total dimension could be dramatically reduced to 23x27x4 mm including wireless BM except for battery. The power isolation was built to avoid the effect of radio-frequency interference on the system as well as to protect brain cells from system damage due to excessive power dissipation or external electric leakage. In vivo performance was evaluated in terms of long-term stability and FIR algorithm for 4 months after implantation. Four TiWiNets were implanted into experimental animals' brains, and single neural signals were recorded and analyzed in real time successfully except for one due to silicon- coated problem. They could control remote target machine by classify neural spike trains based on decoding technology. Thus, we concluded that our study could fulfill in vivo needs to study various single neuron-movement relationships in diverse fields of BMI.
Automatic Data Processing ; Brain ; Brain-Computer Interfaces ; Neural Prostheses ; Organothiophosphorus Compounds ; Signal Processing, Computer-Assisted ; Silanes

Retinal model is an essential part in the retinal prosthesis. Based on the retinal physiology and the experimental data, the model is able to simulate the information processing in the retina, and can be used to investigate the relation between the input image and the neuron firing. We can categorize the models into circuit realization and algorithm realization. This article is a state-of-art review of different types of retinal models.
Algorithms ; Humans ; Models, Biological ; Models, Neurological ; Neural Networks (Computer) ; Prostheses and Implants ; Retina ; anatomy & histology ; physiology

A recently developed machine learning algorithm referred to as Extreme Learning Machine (ELM) was used to classify machine control commands out of time series of spike trains of ensembles of CA1 hippocampus neurons (n=34) of a rat, which was performing a target-to-goal task on a two-dimensional space through a brain-machine interface system. Performance of ELM was analyzed in terms of training time and classification accuracy. The results showed that some processes such as class code prefix, redundancy code suffix and smoothing effect of the classifiers' outputs could improve the accuracy of classification of robot control commands for a brain-machine interface system.
Aniline Compounds ; Animals ; Brain-Computer Interfaces ; Hippocampus ; Learning ; Neural Prostheses ; Neurons ; Rats ; Machine Learning

The method of BP neural network improved by Levenberg-Marquardt algorithm in surface EMG signal classification is proposed. The data reduction and preprocessing operations of the signals are performed by means of the wavelet transform. The classifier can identify four classes of forearm movement: hand extension, hand grasp,forearm pronation and forearm supination with a high accuracy.Experimental result shows that the BP neural netwok improved by LM algorithm has greatly increased the speed and the accuracy of signal classification in practical application of prothesis control.
Algorithms ; Electromyography ; methods ; Forearm ; Hand ; Humans ; Movement ; Neural Networks (Computer) ; Prostheses and Implants

OBJECTIVE: The purpose of this study to develop new deep-brain stimulation system for long-term use in animals, in order to develop a variety of neural prostheses. METHODS: Our system has two distinguished features, which are the fully implanted system having wearable wireless power transfer and ability to change the parameter of stimulus parameter. It is useful for obtaining a variety of data from a long-term experiment. RESULTS: To validate our system, we performed pre-clinical test in Parkinson's disease-rat models for 4 weeks. Through the in vivo test, we observed the possibility of not only long-term implantation and stability, but also free movement of animals. We confirmed that the electrical stimulation neither caused any side effect nor damaged the electrodes. CONCLUSION: We proved possibility of our system to conduct the long-term pre-clinical test in variety of parameter, which is available for development of neural prostheses.
Animals ; Deep Brain Stimulation* ; Electric Stimulation ; Electrodes ; Neural Prostheses ; Parkinson Disease* ; Rodentia*

For successful restoration of visual function by a visual neural prosthesis such as retinal implant, electrical stimulation should evoke neural responses so that the information on visual input is properly represented. A stimulation strategy, which means a method for generating stimulation waveforms based on visual input, should be developed for this purpose. We proposed to use the decoding of visual input from retinal ganglion cell (RGC) responses for the evaluation of stimulus encoding strategy. This is based on the assumption that reliable encoding of visual information in RGC responses is required to enable successful visual perception. The main purpose of this study was to determine the influence of inter-dependence among stimulated RGCs activities on decoding accuracy. Light intensity variations were decoded from multiunit RGC spike trains using an optimal linear filter. More accurate decoding was possible when different types of RGCs were used together as input. Decoding accuracy was enhanced with independently firing RGCs compared to synchronously firing RGCs. This implies that stimulation of independently-firing RGCs and RGCs of different types may be beneficial for visual function restoration by retinal prosthesis.
Electric Stimulation ; Fires ; Light ; Neural Prostheses ; Retinal Ganglion Cells ; Retinaldehyde ; Visual Perception ; Visual Prosthesis

Humans ; Auditory Pathways ; Hearing Loss, Sensorineural ; Cochlear Implantation ; Cochlear Implants ; Hearing Loss, Central ; Auditory Threshold ; Evoked Potentials, Auditory, Brain Stem

For successful visual perception by visual prosthesis using electrical stimulation, it is essential to develop an effective stimulation strategy based on understanding of retinal ganglion cell (RGC) responses to electrical stimulation. We studied RGC responses to repetitive electrical stimulation pulses to develop a stimulation strategy using stimulation pulse frequency modulation. Retinal patches of photoreceptor-degenerated retinas from rd1 mice were attached to a planar multi-electrode array (MEA) and RGC spike trains responding to electrical stimulation pulse trains with various pulse frequencies were observed. RGC responses were strongly dependent on inter-pulse interval when it was varied from 500 to 10 ms. Although the evoked spikes were suppressed with increasing pulse rate, the number of evoked spikes were >60% of the maximal responses when the inter-pulse intervals exceeded 100 ms. Based on this, we investigated the modulation of evoked RGC firing rates while increasing the pulse frequency from 1 to 10 pulses per second (or Hz) to deduce the optimal pulse frequency range for modulation of RGC response strength. RGC response strength monotonically and linearly increased within the stimulation frequency of 1~9 Hz. The results suggest that the evoked neural activities of RGCs in degenerated retina can be reliably controlled by pulse frequency modulation, and may be used as a stimulation strategy for visual neural prosthesis.
Animals ; Electric Stimulation ; Fires ; Heart Rate ; Mice ; Neural Prostheses ; Retina ; Retinal Ganglion Cells ; Retinaldehyde ; Visual Perception ; Visual Prosthesis

BACKGROUND AND OBJECTIVES: Auditory brainstem implantation (ABI) is another option for hearing rehabilitation in non-neurofibromatosis type 2 patients who cannot undergo cochlear implantation (CI). However, the average performance of ABI is worse than that of CI. We analyzed the psycho-electrical parameters of each electrode and psycho-acoustic response to different frequency sounds in nontumor patients with ABI. SUBJECTS AND METHOD: Sixteen patients with ABI from July 2008 to May 2013 were included in the study. They were followed up for 4 to 56 months. Among them, 12 were prelingual deaf with a narrow internal auditory canal or cochlear ossification. The remaining four were post-lingual deaf adults with severely ossified cochleae. We analyzed the electrical parameters [impedance, threshold level (T level), and dynamic range] of each of the 12 electrodes. We also evaluated the sound field pure-tone threshold, Ling 6 sound detection-identification test (Ling 6 test), and pitch ranking data of these patients. RESULTS: The impedance, T level, and dynamic range did not significantly differ among electrodes. However, the pure-tone threshold to sound field stimulation was elevated in the high tone area, where more variables were found than in the low frequency area. Patients could not identify /S/ and /Sh/ sounds in the Ling 6 test. The mean T level and the dynamic range of the three highest pitch-perceiving electrodes in each patient was higher and narrower, respectively, than those of the three lowest pitch-perceiving electrodes. CONCLUSION: The nontumor patients with ABI have difficulty perceiving high pitch sound. More sophisticated penetrating type electrodes and, if possible, bimodal stimulation with CI, could be considered.
Adult ; Auditory Brain Stem Implantation* ; Auditory Brain Stem Implants* ; Cochlea ; Cochlear Implantation ; Cochlear Implants ; Electric Impedance ; Electrodes ; Hearing ; Humans ; Methods ; Rehabilitation