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LOW-COST SHAPING OF ELECTRICAL STIMULATION WAVEFORMS FOR
BIOELECTRONIC MEDICINE WITH IMPROVED EFFICIENCY AND
SELECTIVITY
Amin Rashidi, Francesc Varkevisser, Vasiliki Giagka, Tiago L. Costa, and
Wouter A. Serdijn
Section Bioelectronics, dept. Microelectronics, Delft University of Technology,
Mekelweg 4, 2628 CD Delft,
The Netherlands
ABSTRACT
Electrical stimulation is proven to be an effective way of neuromodulation in bioelectronic medicine
(e.g. cochlear implants, deep brain stimulators, etc.), delivering localized treatment by the means of
electrical pulses. To increase the stimulation efficiency and neural-type selectivity, there is an increasing
interest to employ non-rectangular stimulation waveforms [1-4]. Even though delivering and storing
digital data at the stimulator provides the highest flexibility for generating stimulation waveforms, state-
of-the-art approaches suffer either from poor resolution or the requirement of high data bandwidth for
wirelessly powered implants [2]. Using Analog waveform generators is an alternative approach at the
cost of extra implementation complexity for each type of waveform [3].
To fulfill the same goals as employing arbitrary waveforms for stimulation, we propose to shape the
typical rectangular waveform using a programmable first-order low-pass filter, mimicking the natural
filtering characteristic of the neural membrane. Using bio-realistic modeling, we show that such a pre-
filtered waveform requires less or equal energy for the activation of neurons when compared with other
energy-efficient waveforms (e.g. Gaussian). Notably, this comes at the low cost of only one extra
programmable parameter (i.e., the filter’s corner frequency), on top of the typical duration and amplitude
parameters.
The basic concept of this work is driven by the fact that the natural low-pass characteristic of the
neuron’s membrane limits the energy transfer efficiency from the stimulator to the cell. Thus, it is
proposed to pre-filter the high-frequency components of the stimulus [4]. The method is validated for a
Hodgkin-Huxley (HH) axon-cable model using NEURON v8.0 software. The required activation energy
is simulated for rectangular, Gaussian, half-sine, triangular, ramp-up, and ramp-down waveforms, all
with pulse durations of 10-1000µs, and low-pass filtered with cut-off frequencies of 0.5-50kHz.
Simulations show a 51.5% reduction in the required activation energy for the shortest rectangular pulse
(i.e., 10-μs pulse width) after filtering at 5kHz. It is also shown that the minimum required activation
energy can be decreased by 11.04%, 9.49%, 8.28%, 1.81%, 0.17%, and 0% when an appropriate pre-
filter is applied to the rectangular, ramp-down, ramp-up, half-sine, triangular, and Gaussian waveforms,
respectively. Finally, a perspective usage of this method to improve the selectivity of electrical
stimulation is drawn.
References:
[1] K. Kolovou-Kouri, A. Rashidi, F. Varkevisser, W. A. Serdijn, and V. Giagka, “Energy savings of multi-channel
neurostimulators with non-rectangular current-mode stimuli using multiple supply rails,” in 2022 44th Annual
International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2022, pp. 3443–3446.
[2] G. O’Leary, D. M. Groppe, T. A. Valiante, N. Verma, and R. Genov, “Nurip: Neural interface processor for
brain-state classification and programmable-waveform neurostimulation,” IEEE Journal of Solid-State Circuits,
vol. 53, no. 11, pp. 3150–3162, 2018.
[3] M. H. Maghami, A. M. Sodagar, and M. Sawan, “Versatile stimulation back-end with programmable
exponential current pulse shapes for a retinal visual prosthesis,” IEEE Transactions on Neural Systems and
Rehabilitation Engineering, vol. 24, no. 11, pp. 1243–1253, 2016.
[4] F. Varkevisser, A. Rashidi, T. L. Costa, V. Giagka, and W. A. Serdijn, “Pre-Filtering of Stimuli for Improved
Energy Efficiency in Electrical Neural Stimulation,” in
Proceedings of 2022 IEEE Biomedical Circuits and
Systems Conference(BioCAS)
, 2022, in press.