AIMC Topic: Smartphone

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Coarse-Fine Convolutional Deep-Learning Strategy for Human Activity Recognition.

Sensors (Basel, Switzerland)
In the last decade, deep learning techniques have further improved human activity recognition (HAR) performance on several benchmark datasets. This paper presents a novel framework to classify and analyze human activities. A new convolutional neural ...

Falls Risk Classification of Older Adults Using Deep Neural Networks and Transfer Learning.

IEEE journal of biomedical and health informatics
Prior research in falls risk classification using inertial sensors has relied on the use of engineered features, which has resulted in a feature space containing hundreds of features that are likely redundant and possibly irrelevant. In this paper, w...

Mass Surveilance of -Smartphone-Based DIY Microscope and Machine-Learning-Based Approach for Worm Detection.

Sensors (Basel, Switzerland)
The nematode is often used as an alternative animal model due to several advantages such as morphological changes that can be seen directly under a microscope. Limitations of the model include the usage of expensive and cumbersome microscopes, and r...

Stress detection in daily life scenarios using smart phones and wearable sensors: A survey.

Journal of biomedical informatics
Stress has become a significant cause for many diseases in the modern society. Recently, smartphones, smartwatches and smart wrist-bands have become an integral part of our lives and have reached a widespread usage. This raised the question of whethe...

Accuracy of Samsung Gear S Smartwatch for Activity Recognition: Validation Study.

JMIR mHealth and uHealth
BACKGROUND: Wearable accelerometers have greatly improved measurement of physical activity, and the increasing popularity of smartwatches with inherent acceleration data collection suggest their potential use in the physical activity research domain;...

Navigating Virtual Environments Using Leg Poses and Smartphone Sensors.

Sensors (Basel, Switzerland)
Realization of navigation in virtual environments remains a challenge as it involves complex operating conditions. Decomposition of such complexity is attainable by fusion of sensors and machine learning techniques. Identifying the right combination ...

A smartphone-based system for fluorescence polarization assays.

Biosensors & bioelectronics
This paper demonstrates the use of a smartphone-based sensor for fluorescence polarization (FP) analysis of biomolecules. The FP detection can rapidly sense ligand-analyte bindings by measuring molecule mobility, and thus, FP-based assays have been w...

Smartphone-based fluorescent lateral flow immunoassay platform for highly sensitive point-of-care detection of Zika virus nonstructural protein 1.

Analytica chimica acta
Simple, inexpensive, and rapid diagnostic tests in low-resource settings with limited laboratory equipment and technical expertise are instrumental in reducing morbidity and mortality from epidemic infectious diseases. We developed a smartphone-based...

Measuring Oxygen Saturation With Smartphone Cameras Using Convolutional Neural Networks.

IEEE journal of biomedical and health informatics
Arterial oxygen saturation ([Formula: see text]) is an indicator of how much oxygen is carried by hemoglobin in the blood. Having enough oxygen is vital for the functioning of cells in the human body. Measurement of [Formula: see text] is typically e...