EnsemConvNet: a deep learning approach for human activity recognition using smartphone sensors for healthcare applications

2020 ◽  
Vol 79 (41-42) ◽  
pp. 31663-31690
Author(s):  
Debadyuti Mukherjee ◽  
Riktim Mondal ◽  
Pawan Kumar Singh ◽  
Ram Sarkar ◽  
Debotosh Bhattacharjee
Keyword(s):  
Deep Learning ◽  
Activity Recognition ◽  
Human Activity ◽  
Human Activity Recognition ◽  
Learning Approach ◽  
Healthcare Applications ◽  
Smartphone Sensors

scholarly journals SparseSense: Human Activity Recognition from Highly Sparse Sensor Data-streams Using Set-based Neural Networks

2019 ◽  
Author(s):  
Alireza Abedin ◽  
S. Hamid Rezatofighi ◽  
Qinfeng Shi ◽  
Damith C. Ranasinghe
Keyword(s):  
Deep Learning ◽  
Older People ◽  
Activity Recognition ◽  
Human Activity ◽  
Data Streams ◽  
Sparse Data ◽  
Human Activity Recognition ◽  
Learning Activity ◽  
Healthcare Applications ◽  
Sensing Applications

Batteryless or so called passive wearables are providing new and innovative methods for human activity recognition (HAR), especially in healthcare applications for older people. Passive sensors are low cost, lightweight, unobtrusive and desirably disposable; attractive attributes for healthcare applications in hospitals and nursing homes. Despite the compelling propositions for sensing applications, the data streams from these sensors are characterised by high sparsity---the time intervals between sensor readings are irregular while the number of readings per unit time are often limited. In this paper, we rigorously explore the problem of learning activity recognition models from temporally sparse data. We describe how to learn directly from sparse data using a deep learning paradigm in an end-to-end manner. We demonstrate significant classification performance improvements on real-world passive sensor datasets from older people over the state-of-the-art deep learning human activity recognition models. Further, we provide insights into the model's behaviour through complementary experiments on a benchmark dataset and visualisation of the learned activity feature spaces.

A Statistical and Deep Learning Approach for Human Activity Recognition

2019 ◽  
Author(s):  
Abdul Kadar Muhammad Masum ◽  
Mohammad Emdad Hossain ◽  
Asma Humayra ◽  
Sanzeeda Islam ◽  
Arnab Barua ◽  
...  
Keyword(s):  
Deep Learning ◽  
Activity Recognition ◽  
Human Activity ◽  
Human Activity Recognition ◽  
Learning Approach
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