Human activity recognition (HAR) leverages sensors such as accelerometers and gyroscopes to discern human physical activities, offering transformative insights for smart healthcare applications, from Parkinson's disease monitoring to diabetes management. While deep learning (DL) methods have emerged as frontrunners in HAR using wearable sensors, they often struggle with challenges stemming from long-term dependencies in sequential data and intricate feature extraction from expansive datasets. Addressing these gaps, this paper introduces a novel ensemble-based deep neural network that seamlessly integrates four distinct classifiers: CNN-LSTM, LSTM-CNN, CNN-BiLSTM, and BiLSTM-CNN. This combination enhances feature extraction and captures the detailed long-term patterns that have been challenging for traditional HAR models. By also using ensemble learning, our model becomes more consistent and reliable in its predictions. Benchmark evaluations on mHealth, UCI-HAR, and WISDM datasets validate the model's superiority, with accuracy scores of 99.91%, 98.10%, and 99.48% respectively. Further, the k-fold cross-validation technique is used to assess the performance results in terms of the mean F1-score, mean accuracy at k = 5. These compelling results underscore the model's capacity to address the inherent limitations of existing HAR systems, positioning it as a groundbreaking tool for advanced human activity recognition in smart healthcare scenarios.

Vaibhav Soni

Himanshu Yadav

Vijay Bhaskar Semwal

Sudhakar Tripathi

IETE Journal of Research

IETE JOURNAL OF RESEARCH 是由印度电子和电信工程师学会 (IETE) 出版的双月刊。它发表描述原始研究工作或新产品/工艺开发的科学和技术论文。偶尔会针对新的和新兴的研究领域提出特殊问题。 IETE 研究期刊对有兴趣跟踪在电子、电信、计算机科学与工程和信息技术等广泛领域进行的原始研究和开发工作的研究人员、工程师、科学家、教师、管理人员和学生很有用.

IETE Journal of Research is a bi-monthly publication by the Institution of Electronics and Telecommunication Engineers (IETE) in India. It publishes scientific and technical papers that describe original research work or the development of new products/processes. Special issues may occasionally be dedicated to new and emerging research areas. The IETE Journal of Research is valuable for researchers, engineers, scientists, educators, managers, and students interested in tracking original research and development work across a wide range of fields, including electronics, telecommunications, computer science and engineering, and information technology.

IETE Journal of Research 是由印度电子和电信工程师学会 (IETE) 出版的双月刊。该期刊发表关于原始研究工作或新产品/工艺开发的科学和技术论文。偶尔会针对新的和新兴的研究领域发布特刊。IETE Journal of Research 对于希望跟踪电子、电信、计算机科学与工程以及信息技术等广泛领域的原始研究和开发工作的研究人员、工程师、科学家、教师、管理人员和学生非常有价值。

Category	Quartile
计算机科学	4
计算机科学, 工程电子与电气	4
计算机科学, 电信学	4

Improving Human Activity Recognition in Smart Healthcare with Ensemble Deep Learning

ivySCI AI Smartly Parses PDF, Answers Researchers' Questions, and Helps You Understand Papers in Seconds

Journal Info