Mohamed Elgendi
Datos Biográficos
| ID | 7592467 |
|---|---|
| NOMBRE | Mohamed Elgendi |
| NOMBRES | Mohamed |
| APELLIDO | Elgendi |
| FIRMA | ELGENDI M |
| AFILIACIONES | ETH Zurich |
| ORCID | 0000-0003-1831-0202 |
| VERIFICADO | Sí |
| TOTAL DE OBRAS | 3 |
| TOTAL DE CITAS | 0 |
| OBRAS COMO AUTOR | 3 |
| OBRAS COMO EDITOR | 0 |
| PRIMER AÑO DE PUBLICACIÓN | 2015 |
| AÑO MÁS RECIENTE DE PUBLICACIÓN | 2023 |
| ÍNDICE H | 0 |
The use of deep learning for smartphone-based human activity recognition
The emerging field of digital phenotyping leverages the numerous sensors embedded in a smartphone to better understand its user's current psychological state and behavior, enabling improved health support systems for patients. As part of this work, a common task is to use the smartphone accelerometer to automatically recognize or classify the behavior of the user, known as human activity recognition (HAR). In this article, we present a deep learn…
Fall detection using accelerometer-based smartphones
According to World Health Organization statistics, falls are the second leading cause of unintentional injury deaths worldwide. With older people being particularly vulnerable, detecting, and reporting falls have been the focus of numerous health technology studies. We screened 267 studies and selected 15 that detailed pervasive fall detection and alerting apps that used smartphone accelerometers. The fall datasets used for the analyses included …
Towards Investigating Global Warming Impact on Human Health Using Derivatives of Photoplethysmogram Signals
Recent clinical studies show that the contour of the photoplethysmogram (PPG) wave contains valuable information for characterizing cardiovascular activity. However, analyzing the PPG wave contour is difficult; therefore, researchers have applied first or higher order derivatives to emphasize and conveniently quantify subtle changes in the filtered PPG contour. Our hypothesis is that analyzing the whole PPG recording rather than each PPG wave con…
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Towards Investigating Global Warming Impact on Human Health Using Derivatives of Photoplethysmogram Signals
Recent clinical studies show that the contour of the photoplethysmogram (PPG) wave contains valuable information for characterizing cardiovascular activity. However, analyzing the PPG wave contour is difficult; therefore, researchers have applied first or higher order derivatives to emphasize and conveniently quantify subtle changes in the filtered PPG contour. Our hypothesis is that analyzing the whole PPG recording rather than each PPG wave con…
Fall detection using accelerometer-based smartphones
According to World Health Organization statistics, falls are the second leading cause of unintentional injury deaths worldwide. With older people being particularly vulnerable, detecting, and reporting falls have been the focus of numerous health technology studies. We screened 267 studies and selected 15 that detailed pervasive fall detection and alerting apps that used smartphone accelerometers. The fall datasets used for the analyses included …
The use of deep learning for smartphone-based human activity recognition
The emerging field of digital phenotyping leverages the numerous sensors embedded in a smartphone to better understand its user's current psychological state and behavior, enabling improved health support systems for patients. As part of this work, a common task is to use the smartphone accelerometer to automatically recognize or classify the behavior of the user, known as human activity recognition (HAR). In this article, we present a deep learn…
Computer Science (3 obras) · Artificial Intelligence (2 obras) · Context-Aware Activity Recognition Systems (2 obras) · Machine learning (2 obras) · Medicine (2 obras) · Mobile Health and mHealth Applications (2 obras) · Non-Invasive Vital Sign Monitoring (2 obras) · Accelerometer (1 obra) · Activity recognition (1 obra) · Applied Psychology (1 obra)