An energy-efficient, dynamic voltage scaling neural stimulator for a proprioceptive prosthesis

Williams, Ian; Constandinou, Timothy G.

doi:10.1109/iscas.2012.6271420

Cited by 15 publications

(23 citation statements)

References 33 publications

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“…It is known that the voltage-mode stimulation provides the highest PE 19,20 because ideally, V load equals to V stim at the output stage of the stimulator. [22][23][24] For PE of current-mode stimulator, also considering the output current branch as the output stage only, the PE is expressed as The charge-mode stimulation as shown in Figure 1C has accurate control over the amount of injected charge.…”

Section: Analysis and Optimization Of Power Efficiency In Stimulatorsmentioning

confidence: 99%

“…The above-mentioned deficiencies of voltage-mode and charge-mode stimulation methods make the current-mode stimulation the most widely adopted method in stimulator designs. [22][23][24] For PE of current-mode stimulator, also considering the output current branch as the output stage only, the PE is expressed as…”

Section: Analysis and Optimization Of Power Efficiency In Stimulatorsmentioning

confidence: 99%

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A power‐efficient current‐mode neural/muscular stimulator design for peripheral nerve prosthesis

Liu

Yao

et al. 2017

Circuit Theory & Apps

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This paper presents a 16-channel power-efficient neural/muscular stimulation integrated circuit for peripheral nerve prosthesis. First, the theoretical analysis is presented to show the power efficiency optimization in a stimulator. Moreover, a continuous-time, biphasic exponential-current-waveform generation circuit is designed based on Taylor series approximation and implemented in the proposed stimulation chip to optimize the power efficiency. In the 16-channel stimulator chip design, each channel of the stimulator consists of a current copier, an exponential current generator, an active charge-balancing circuit, and a 24-V output stage. Stimulation amplitude, pulse width, and frequency can be set and adjusted through an external field-programmable gate array by sending serial commands. Finally, the proposed stimulator chip has been fabricated in a 0.18-μm advanced complementary metal-oxide-semiconductor process with 24-V laterally diffused metal oxide semiconductor option. The maximum stimulation power efficiency of 95.9% is achieved at the output stage with an electrode model of 10-kΩ resistance and 100-nF capacitance. Animal experiment results further demonstrate the power efficiency improvement and effectiveness of the stimulator.

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Section: Analysis and Optimization Of Power Efficiency In Stimulatorsmentioning

confidence: 99%

Section: Analysis and Optimization Of Power Efficiency In Stimulatorsmentioning

confidence: 99%

A power‐efficient current‐mode neural/muscular stimulator design for peripheral nerve prosthesis

Liu

Yao

et al. 2017

Circuit Theory & Apps

View full text Add to dashboard Cite

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“…(3) H-bridge with multiple current sinks [80]. This approach assumes an asymmetric biphasic waveform.…”

Section: Charge-balanced Stimulationmentioning

confidence: 99%

“…However, if the current sink that is active in the anodic phase is sequentially changed after each stimulus waveform, then after cycles each sink would have been active for the same amount of time during the cathodic and anodic phases, yielding accurate charge balance. The method is claimed to achieve a maximum charge mismatch of 0.45% [80].…”

Section: Charge-balanced Stimulationmentioning

confidence: 99%

Advances in Microelectronics for Implantable Medical Devices

Demosthenous

2014

Advances in Electronics

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Implantable medical devices provide therapy to treat numerous health conditions as well as monitoring and diagnosis. Over the years, the development of these devices has seen remarkable progress thanks to tremendous advances in microelectronics, electrode technology, packaging and signal processing techniques. Many of today's implantable devices use wireless technology to supply power and provide communication. There are many challenges when creating an implantable device. Issues such as reliable and fast bidirectional data communication, efficient power delivery to the implantable circuits, low noise and low power for the recording part of the system, and delivery of safe stimulation to avoid tissue and electrode damage are some of the challenges faced by the microelectronics circuit designer. This paper provides a review of advances in microelectronics over the last decade or so for implantable medical devices and systems. The focus is on neural recording and stimulation circuits suitable for fabrication in modern silicon process technologies and biotelemetry methods for power and data transfer, with particular emphasis on methods employing radio frequency inductive coupling. The paper concludes by highlighting some of the issues that will drive future research in the field.

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“…a neural implant which would mimic the function of the human proprioceptive system in the same way a cochlear implant mimics the function of the human auditory system. A proprioceptive prosthesis is envisaged to broadly consist of 3 parts: (1) sensors fitted to a prosthetic limb to track its position, motion and the forces exerted on it; (2) processing that translates the sensor data into neural signal patterns that mimic those produced by proprioceptive receptors found in the human body; and (3) an implanted neural stimulator [3] to "transmit" these artificial neural patterns into the user's peripheral nervous Fig. 1.…”

Section: Introductionmentioning

confidence: 99%

Modelling muscle spindle dynamics for a proprioceptive prosthesis

Williams

Constandinou

2013

2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

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Abstract-Muscle spindles are found throughout our skeletal muscle tissue and continuously provide us with a sense of our limbs' position and motion (proprioception). This paper advances a model for generating artificial muscle spindle signals for a prosthetic limb, with the aim of one day providing amputees with a sense of feeling in their artificial limb. By utilising the Opensim biomechanical modelling package the relationship between a joint's angle and the length of surrounding muscles is estimated for a prosthetic limb. This is then applied to the established Mileusnic model to determine the associated muscle spindle firing pattern. This complete system model is then reduced to allow for a computationally efficient hardware implementation. This reduction is achieved with minimal impact on accuracy by selecting key monoarticular muscles and fitting equations to relate joint angle to muscle length. Parameter values fitting the Mileusnic model to human spindles are then proposed and validated against previously published human neural recordings. Finally, a model for fusimotor signals is also proposed based on data previously recorded from reduced animal experiments.

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An energy-efficient, dynamic voltage scaling neural stimulator for a proprioceptive prosthesis

Cited by 15 publications

References 33 publications

A power‐efficient current‐mode neural/muscular stimulator design for peripheral nerve prosthesis

A power‐efficient current‐mode neural/muscular stimulator design for peripheral nerve prosthesis

Advances in Microelectronics for Implantable Medical Devices

Modelling muscle spindle dynamics for a proprioceptive prosthesis

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