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The prototype of an electronic bi-directional interface between the Peripheral Nervous System (PNS) and a neuro-controlled hand prosthesis is presented. The system is composed of 2 integrated circuits: a standard CMOS device for neural recording and a HVCMOS device for neural stimulation. The integrated circuits have been realized in 2 different 0....
Citations
... However, cortical recordings are invasive or, when noninvasive, characterized by poor signal-to-noise ratio. Nerve electrodes provide low-amplitude compound signals originating from several muscles and can potentially damage the nerve [15,16]. With respect to the nerve, the muscle provides a noninvasive or less invasive interface and allows detecting signals that contain only the descending efferent information (while in nerves the afferent component is also present), thus facilitating the signal processing necessary for neural decoding. ...
Neuroprostheses may be used to substitute motor functions that are impaired as a result of injury or disease. Surface electromyography (EMG) is currently the most common clinical approach for extracting the user intent and for controlling prosthetics. In commercial control systems, the EMG amplitude is used for single degrees of freedom activation (direct control). However, this simple user interface neglects the full bandwidth of the neural drive to muscle underlying the EMG signal generation. Recent advances in technology for recording and processing EMG signals have been exploited to provide human-machine interfaces based on the neural output from the spinal cord, as decoded from the EMG. This chapter reviews technologies for detecting the activity of large populations of spinal motor neurons from muscle recordings with the aim of advancing clinically viable neuroprosthetics. We focus on invasive and noninvasive interfaces to record the muscle electrical activity and on deconvolution methods for extracting motor neuron discharge timings from these recordings. Finally, we report on two representative applications of this approach in the area of active prostheses (neurotechnologies for substitution) and pathological tremor suppression (neurotechnologies for neuromodulation).
... The signals were recorded with respect to an external ground placed 1 cm proximally from the intraneural electrode. Data was acquired using a custom neural signal acquisition module featuring eight channels, each one implementing a low-noise front-end and an analog-to-digital converter (ADC) (56,57). The input stage provides a gain of 43 dB with an input-referred noise of 2.97 µVrms in the bandwidth between 1.67 mHz and 8 kHz, taking into account the whole signal path including the ADC. ...
Objective:
Among the different approaches for denoising neural signals, wavelet-based methods are widely used due to their ability to reduce in-band noise. All wavelet denoising algorithms have a common structure, but their effectiveness strongly depends on several implementation choices, including the mother wavelet, the decomposition level, the threshold definition, and the way it is applied (i.e., the thresholding). In this work, we investigated these factors to quantitatively assess their effects on neural signals in terms of noise reduction and morphology preservation, which are important when spike sorting is required downstream.
Approach:
Based on the spectral characteristics of the neural signal, according to the sampling rate of the signals, we considered two possible decomposition levels and identified the best-performing mother wavelet. Then, we compared different threshold estimation and thresholding methods and, for the best ones, we also evaluated their effect on clearing the approximation coefficients. The assessments were performed on synthetic signals that had been corrupted by different types of noise and on a murine peripheral nervous system dataset, both of which were sampled at about 16 kHz. The results were statistically analysed in terms of their Pearson's correlation coefficients, root-mean-square errors, and signal-to-noise ratios.
Main results:
As expected, the wavelet implementation choices greatly influenced the processing performance. Overall, the Haar wavelet with a 5-level decomposition, hard thresholding method, and the threshold proposed by Han et al. (2007) achieved the best outcomes. Based on the adopted performance metrics, wavelet denoising with these parametrizations outperformed conventional 300-3000 Hz linear bandpass filtering.
Significance:
These results can be used to guide the reasoned and accurate selection of wavelet denoising implementation choices in the context of neural signal processing, particularly when spike-morphology preservation is required.
... Comparing to the first model, this model requires more power 16 . ...
Objectives: To design and develop a Wireless device for Deep Brain Stimulation studies in Rat Model. Methods/ Statistical Analysis: In order to model the design, we have used ASIC (Application Specified) and Off the Shelf Components that helps the device Cheap and portable. We have designed the device using Allegro PCB Design and OrCad. Findings: Before the real time execution in rat models, we tested our device in vitro. Device is observed using oscilloscope. We ensured the life time of the device that can extend up to 90 days. In comparing with other commercial stimulators, this device has long duration of life time with high accuracy in delivering output pulses and less expensive. In order to show the reliability, we have included complete schematics and market price of the components used. Application/Improvements: The current device can be made use to deliver Unbalanced Biphasic Output Pulses.
... Recent advances in microelectronics have enabled the development of small size, reliable, low power and low cost implantable medical devices (IMDs) [1]. These implantable devices offer a wide range of applications, especially in prostheses used for suppressing the debilitating effects of neurological disorders such as Parkinson's and epilepsy [2]. Neural prosthetic devices can significantly improve the quality of life for neuro-patients and their families, a special attention should be paid to provide the desired characteristics of these micro-systems [3]. ...
This paper introduces a high precision analog multiplexer to be used in multi-channel neural recording micro-systems. In any time-division multiplexing (TDM) system, the accuracy of the analog switches within the mul-tiplexer is a critical parameter to determine overall performance of the system. To satisfy the accuracy requirements of the switch, a novel technique to minimize the charge injection and clock feed-through errors by using a very simple structure is proposed. Moreover, an innovative approach to increase the off-resistance of the switch and consequently minimizing its leakage current is presented. In order to evaluate the performance of the proposed switch, simulations are done in a 0.18 μm standard CMOS technology. Simulation results show that switch induced errors are significantly eliminated by using the proposed cancellation technique. The output error charge due to charge injection and clock feed-through over a wide range of the input signal variation is very low (less than 1.53 fC). Also Simulation results show that the proposed switch achieves signal to noise plus distortion ratio (SNDR) of 100.6 dB, effective number of bits (ENOB) of 16.42, total harmonic distortion (THD) of −100.88 dB and spurious-free dynamic range (SFDR) of 101.47 dB for a 1 kHz sinusoidal input of 800 mv peak-to-peak amplitude at 20 kHz sampling rate with a 1.8 V supply voltage. In addition to the switched induced errors, special care has to be taken with regard to the crosstalk effects while designing of the analog multiplexers. In this work, by using an appropriate analog switch with considering crosstalk requirements, using suitable buffers prior to the multiplexer input channels and designing a proper layout, the total crosstalk between adjacent channels is negligible. The post layout simulation of crosstalk shows that the total crosstalk at a sampling rate of 20 kHz per channel is less than −80 dB.
... Fig. 1 shows how the three chips operate. The voltage booster, described in [9], is in charge of raising the 3.3V supply voltage up to 17V in order to allow to inject currents in the order of hundreds of microampere into an electrode that can show an impendance in the order of tens of kilohms. Voltage boosting is controlled by the stimulation chip that constantly monitors the high-voltage supply and starts/stops the booster when needed. ...
... Voltage boosting is controlled by the stimulation chip that constantly monitors the high-voltage supply and starts/stops the booster when needed. The stimulation chip [9] generates the stimulation currents that are digitally programmable in terms of amplitude, frequency, width and shape. The amplitude can range from 10µA to 310µA in low current mode and from from 17.5µA to 540µA in high current mode. ...
... Despite these challenges, we believe the proposed scheme is more promising than current alternative research pathways. For example, an alternative approach is the direct recording from efferent fibers in peripheral nerves (Micera et al., 2011;Carboni et al., 2016;Ng et al., 2016), which however presents problems related to low signal amplitude and signal-to-noise ratio, small number of identified spike patterns, and potential intraneural damage (Navarro et al., 2005;Carboni et al., 2016). In comparison, the presented strategy may provide a safer and more robust method to operate modern prostheses with functions closer to the biological ones. ...
... Despite these challenges, we believe the proposed scheme is more promising than current alternative research pathways. For example, an alternative approach is the direct recording from efferent fibers in peripheral nerves (Micera et al., 2011;Carboni et al., 2016;Ng et al., 2016), which however presents problems related to low signal amplitude and signal-to-noise ratio, small number of identified spike patterns, and potential intraneural damage (Navarro et al., 2005;Carboni et al., 2016). In comparison, the presented strategy may provide a safer and more robust method to operate modern prostheses with functions closer to the biological ones. ...
Modern robotic hands/upper limbs may replace multiple degrees of freedom of extremity function. However, their intuitive use requires a high number of control signals, which current man-machine interfaces do not provide. Here, we discuss a broadband control interface that combines targeted muscle reinnervation, implantable multichannel electromyographic sensors, and advanced decoding to address the increasing capabilities of modern robotic limbs. With targeted muscle reinnervation, nerves that have lost their targets due to an amputation are surgically transferred to residual stump muscles to increase the number of intuitive prosthetic control signals. This surgery re-establishes a nerve-muscle connection that is used for sensing nerve activity with myoelectric interfaces. Moreover, the nerve transfer determines neurophysiological effects, such as muscular hyper-reinnervation and cortical reafferentation that can be exploited by the myoelectric interface. Modern implantable multichannel EMG sensors provide signals from which it is possible to disentangle the behavior of single motor neurons. Recent studies have shown that the neural drive to muscles can be decoded from these signals and thereby the user's intention can be reliably estimated. By combining these concepts in chronic implants and embedded electronics, we believe that it is in principle possible to establish a broadband man-machine interface, with specific applications in prosthesis control. This perspective illustrates this concept, based on combining advanced surgical techniques with recording hardware and processing algorithms. Here we describe the scientific evidence for this concept, current state of investigations, challenges, and alternative approaches to improve current prosthetic interfaces.
... The signal at the output of the buffer is fed into a Σ∆ modulator to be converted into a 1-bit digital stream. [7]. Finally, the 1-bit modulator outputs of the eight channels are encoded by the digital interface module and transmitted to the FPGA by a Serial Peripheral Interface (SPI). ...
A biomedical interface that combines into a single and compact device the recording of biopotentials and the electrical stimulation of neural fibres is presented. It is intended for enabling the control over a robotic hand and for restoring the sensory feedback in amputees by directly interfacing the peripheral nervous system (PNS) in closed-loop. A modular system consisting in one or more independent 16-channels bidirectional units was conceived. Each module is based on three 0.35μm bulk-CMOS integrated circuits (ICs): a recording unit, a High-Voltage (HV) stimulator and a HV booster. A tunable bandwidth (10Hz-8kHz) allows the recording IC to acquire both electroneurographyc (ENG) and electromiographyc (EMG) signals with a programmable gain up to 43.5dB. The signals are then converted into a digital domain by means of a ΣΔ converter. Due to the typical high impedance at the electrode-tissue interface, a programmable HV booster that increases the stimulation voltage up to 19V was designed. It is directly controlled by the stimulation module that generates current-based pulses with a programmable amplitude and pulse-width. The whole system was validated by means of in-vivo experiments in rats.
... Variations in the filter response can therefore lead to situations in which the disturbance is not properly filtered or in which the useful signal is attenuated. In recent years PNS interfaces have regained popularity, especially in neuroprosthetics, as they allow achieving excellent results [3], [4] reducing at the same time the invasivity compared to CNS (Central Nervous System) ones that imply electrodes implanted inside the skull. There is therefore the need for circuits that allow designing high precision very low frequency filters. ...
In this paper a novel Pseudo Resistor bias scheme capable of achieving improved performances against process parameters variations is presented. The use of a matched structure allows achieving a simulated statistical variation σ/μ one order of magnitude better than conventional bias schemes proposed in literature. The entire circuit was designed to be able to emulate a tunable resistor whose resistance could be digitally set in the range 400 MΩ - 90 GΩ. The design of a very low frequency BPF for biopotential recording was also covered as a suitable application. The tunability offered by the bias scheme was employed, in this case, to realize a high-pass cut-off frequency variable in the range 10 Hz-2 kHz. An integrated circuit including 8 acquisition channels, each of which is composed of the designed BPF and a conventional 10 bit ADC, was finally realized in a CMOS 0.35 μm process. The chip was successfully tested showing a measured σ/μ variation of the high-pass cutoff frequency equal to 0.13 when different channels on the same die are considered.
Objective:
This paper describes the design, testing and use of a novel multichannel block-capable stimulator for acute neurophysiology experiments to study highly selective neural interfacing techniques. This paper demonstrates the stimulator's ability to excite and inhibit nerve activity in the rat sciatic nerve model concurrently using monophasic and biphasic nerve stimulation as well as high-frequency alternating current (HFAC).
Approach:
The proposed stimulator uses a Howland Current Pump circuit as the main analogue stimulator element. 4 current output channels with a common return path were implemented on printed circuit board using Commercial Off-The-Shelf components. Programmable operation is carried out by an ARM Cortex-M4 Microcontroller on the Freescale freedom development platform (K64F).
Main results:
This stimulator design achieves +-10 mA of output current with +-15 V of compliance and less than 6 uA of resolution using a quad-channel 12-bit external DAC, for four independently driven channels. This allows the stimulator to carry out both excitatory and inhibitory (HFAC block) stimulation. DC Output impedance is above 1 Mohm. Overall cost for materials i.e. PCB boards and electronic components is less than USD 450 or GBP 350 and device size is approximately 9 cm x 6 cm x 5 cm.
Significance:
Experimental neurophysiology often requires significant investment in bulky equipment for specific stimulation requirements, especially when using HFAC block. Different stimulators have limited means of communicating with each other, making protocols more complicated. This device provides an effective solution for multi-channel stimulation and block of nerves, enabling studies on selective neural interfacing in acute scenarios with an affordable, portable and space-saving design for the laboratory. The stimulator can be further upgraded with additional modules to extend functionality while maintaining straightforward programming and integration of functions with one controller. Additionally, all source files including all code and PCB design files are freely available to the community to use and further develop.
