# Ultra Low Power Computing for Next Generation Implantable Smart Cardiac Pacemakers

> **NIH NIH SC3** · UNIVERSITY OF TEXAS SAN ANTONIO · 2020 · $110,250

## Abstract

Title: Ultra Low Energy Computing for Next Generation
 Implantable Smart Cardiac Pacemakers
Project Summary
Cardiovascular diseases are one of the major causes of all human deaths. Arrhythmia related human cardiac
mortality and morbidity can be reduced by the implantable artificial pacemakers that are designed to monitor
the cardiac status and to regulate the beating of the heart. Not many years ago, the functionality of a
pacemaker was mostly limited to monitoring signals from the heart and assisting its operation via artificial
pacing when any predefined abnormality was detected. Recently, pacemaker manufacturers have started
incorporating advanced features to make the pacemaker smarter and more user friendly. With low energy
wireless connectivity, the pacemakers can be programmed to automatically activate alerts to the cardiologist or
to the hospital via the connected smart phone or network when an emergency occurs. In the future, the
wireless connectivity may also enable the cardiologist to remotely adjust the settings of the pacemaker to
address the emergency or to recommend other corrective measures. Unfortunately all the added new features
come at the expense of increased power consumption. Also, the wireless connectivity of the implantable
devices opens up the possibility of hacking. In the case of pacemakers a hacker will be able to maliciously
reprogram the pacemaker. These device security threats lead to the need for secure communication channels.
The entire computational task inside a pacemaker is done by a dedicated processor. The upcoming generation
of pacemakers is expected to both diversify the processor work-load and demand significantly increased
computational capabilities. This research aims to develop low-energy computation methods and design
methodologies that can enable future cardiac pacemakers to become a reality. A novel concept of dynamic
computing is developed as a part of this research which will enable the reduction of pacemaker power
consumption by detecting and eliminating repetitions of low level arithmetic/logical operations both in software
and hardware implementations. By identifying overlapping computational steps and predictable data flow
patterns present in most implantable cardiac pacemaker workloads, the proposed design methodologies
promise enhanced performance and improvement in battery life. Applicability of the developed techniques will
be investigated and tested in the context of pacemaker signal processing, security, and reliability workloads.
Nearly 225,000 permanent pacemakers are implanted annually in the United States. The battery in a
pacemaker can last 8-10 years and the pacemaker itself is replaced during a surgical procedure. The
development of ultra-low energy computing techniques for pacemakers is expected to extend the battery life
further, which in turn will reduce the frequency of the surgical procedures needed to replace the pacemaker.
The reduced number of surgical procedures will also ...

## Key facts

- **NIH application ID:** 9853024
- **Project number:** 5SC3GM122735-03
- **Recipient organization:** UNIVERSITY OF TEXAS SAN ANTONIO
- **Principal Investigator:** Eugene B John
- **Activity code:** SC3 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $110,250
- **Award type:** 5
- **Project period:** 2018-02-15 → 2022-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9853024

## Citation

> US National Institutes of Health, RePORTER application 9853024, Ultra Low Power Computing for Next Generation Implantable Smart Cardiac Pacemakers (5SC3GM122735-03). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/9853024. Licensed CC0.

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