Artificial Intelligence in Developing Assistive Devices for the Elderly the Smart Cane Model

With the rapid growth of artificial intelligence (AI), a new generation of innovative assistive devices has been developed for elderly people to enhance their mobility and safety, such the Smart Cane, a system built with a Long Short-Term Memory (LSTM) model to improve mobility, prevent falls, and provide real-time assistance. This research combines mobility tracking metrics, device feedback from the users, and system performance to demonstrate the impact of the Smart Cane. The outcome shows a significant increase in mobility, such (MII jumped from 50-65 to 75-90), 89% falls prevention accuracy, and a very high satisfaction score (4.6/5). The results indicate that LSTM assistive models may have profound implications for the independence and well-being of elderly individuals. Continuing technological development and cost-effectiveness remain prerequisites for maintenance and are potential future delivery methods made possible by IOT and continuous health monitoring, the study shows. This study adds to the emerging field of AI-driven mobility solutions and serves as a steppingstone towards continued progress in assistive technology.

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Published
2025-04-05
DOI
https://doi.org/10.1109/icmi65310.2025.11141099
Primary Topic
Smart Cities and Technologies
Type
article
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article

Artificial Intelligence in Developing Assistive Devices for the Elderly the Smart Cane Model

Hisham Zamil Hamdan, Zaiydoon Khalaf Jabbar
Smart Cities and Technologies
article

Artificial Intelligence in Developing Assistive Devices for the Elderly the Smart Cane Model

Hisham Zamil Hamdan, Zaiydoon Khalaf Jabbar
article en

Abstract

With the rapid growth of artificial intelligence (AI), a new generation of innovative assistive devices has been developed for elderly people to enhance their mobility and safety, such the Smart Cane, a system built with a Long Short-Term Memory (LSTM) model to improve mobility, prevent falls, and provide real-time assistance. This research combines mobility tracking metrics, device feedback from the users, and system performance to demonstrate the impact of the Smart Cane. The outcome shows a significant increase in mobility, such (MII jumped from 50-65 to 75-90), 89% falls prevention accuracy, and a very high satisfaction score (4.6/5). The results indicate that LSTM assistive models may have profound implications for the independence and well-being of elderly individuals. Continuing technological development and cost-effectiveness remain prerequisites for maintenance and are potential future delivery methods made possible by IOT and continuous health monitoring, the study shows. This study adds to the emerging field of AI-driven mobility solutions and serves as a steppingstone towards continued progress in assistive technology.

Mustansiriyah University (IQ), Middle Technical University (IQ)
Openalex Percentile: Top 65%
Smart Cities and Technologies
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Artificial Intelligence in Developing Assistive Devices for the Elderly the Smart Cane Model — Hisham Zamil Hamdan, Zaiydoon Khalaf Jabbar · (2025) | TGRS Research Map | TGRS