Handheld AI CPR Assistive Device with Location Tracking Capability

This paper proposes a handheld AI CPR assitive device estimating chest compression depth with location tracking capability. By using a model of Convolutional Neural Networks (CNN) combined with Long Short-Term Memory (LSTM) networks.

Authors

Jae-Young Pyun (ORCID: https://orcid.org/0000-0002-1143-8281)
Daeho Kim (ORCID: https://orcid.org/0000-0003-4097-4582)
Hyun-Woong Choo

Institutions

Chosun University (KR)

Publication Details

Published: 2025-01-10
DOI: https://doi.org/10.1109/ccnc54725.2025.10976182
Primary Topic: IoT-based Smart Home Systems
Type: article
Field-Weighted Citation Impact: 0.00

Funders

National Research Foundation of Korea

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article

Handheld AI CPR Assistive Device with Location Tracking Capability

Jae-Young Pyun, Daeho Kim, Hyun-Woong Choo

Jan 10, 2025

IoT-based Smart Home Systems

article

Handheld AI CPR Assistive Device with Location Tracking Capability

Jae-Young Pyun, Daeho Kim, Hyun-Woong Choo

January 10, 2025article en

Abstract

Chosun University (KR)

National Research Foundation of Korea

Openalex Percentile: Top 92%

IoT-based Smart Home Systems

DOI Source OpenAlex

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Handheld AI CPR Assistive Device with Location Tracking Capability — Jae-Young Pyun, Daeho Kim, et al. · (2025) | TGRS Research Map | TGRS