A survey on recent advances in wearable fall detection systems
A Ramachandran, A Karuppiah - BioMed research international, 2020 - Wiley Online Library
With advances in medicine and healthcare systems, the average life expectancy of human
beings has increased to more than 80 yrs. As a result, the demographic old‐age …
beings has increased to more than 80 yrs. As a result, the demographic old‐age …
[HTML][HTML] SmartFall: A smartwatch-based fall detection system using deep learning
This paper presents SmartFall, an Android app that uses accelerometer data collected from
a commodity-based smartwatch Internet of Things (IoT) device to detect falls. The …
a commodity-based smartwatch Internet of Things (IoT) device to detect falls. The …
Edge-AI in LoRa-based health monitoring: Fall detection system with fog computing and LSTM recurrent neural networks
JP Queralta, TN Gia, H Tenhunen… - … and signal processing …, 2019 - ieeexplore.ieee.org
Remote healthcare monitoring has exponentially grown over the past decade together with
the increasing penetration of Internet of Things (IoT) platforms. IoT-based health systems …
the increasing penetration of Internet of Things (IoT) platforms. IoT-based health systems …
[HTML][HTML] A study on the application of convolutional neural networks to fall detection evaluated with multiple public datasets
Due to the repercussion of falls on both the health and self-sufficiency of older people and
on the financial sustainability of healthcare systems, the study of wearable fall detection …
on the financial sustainability of healthcare systems, the study of wearable fall detection …
[HTML][HTML] Wearable fall detector using recurrent neural networks
F Luna-Perejón, MJ Domínguez-Morales… - Sensors, 2019 - mdpi.com
Falls have become a relevant public health issue due to their high prevalence and negative
effects in elderly people. Wearable fall detector devices allow the implementation of …
effects in elderly people. Wearable fall detector devices allow the implementation of …
Wearables and deep learning classify fall risk from gait in multiple sclerosis
BM Meyer, LJ Tulipani, RD Gurchiek… - IEEE journal of …, 2020 - ieeexplore.ieee.org
Falls are a significant problem for persons with multiple sclerosis (PwMS). Yet fall prevention
interventions are not often prescribed until after a fall has been reported to a healthcare …
interventions are not often prescribed until after a fall has been reported to a healthcare …
[HTML][HTML] NT-FDS—A noise tolerant fall detection system using deep learning on wearable devices
Given the high prevalence and detrimental effects of unintentional falls in the elderly, fall
detection has become a pertinent public concern. A Fall Detection System (FDS) gathers …
detection has become a pertinent public concern. A Fall Detection System (FDS) gathers …
Applying deep learning technology for automatic fall detection using mobile sensors
With improved quality of life, many countries are facing a serious aging problem. Falls, one
of the most common issues affecting the health of the elderly, are likely to cause irreversible …
of the most common issues affecting the health of the elderly, are likely to cause irreversible …
[HTML][HTML] Towards effective detection of elderly falls with CNN-LSTM neural networks
Fall detection is a very challenging task that has a clear impact in the autonomous living of
the elderly individuals: suffering a fall with no support increases the fears of the elderly …
the elderly individuals: suffering a fall with no support increases the fears of the elderly …
[HTML][HTML] A novel hybrid deep neural network to predict pre-impact fall for older people based on wearable inertial sensors
Falls in the elderly is a major public health concern due to its high prevalence, serious
consequences and heavy burden on the society. Many falls in older people happen within a …
consequences and heavy burden on the society. Many falls in older people happen within a …