Search Results
Human Activity Recognition Based on Wearable Sensor Data: A Standardization of the State-of-the-Art
Inspired by this, we conduct an extensive set of experiments that analyze different sample generation processes and validation protocols to indicate the vulnerable points in human activity recognition based on wearable sensor data.
Continual Learning in Sensor-based Human Activity Recognition: an Empirical Benchmark Analysis
This paper aims to assess to what extent such continual learning techniques can be applied to the HAR domain.
Wearable Sensor-Based Human Activity Recognition with Transformer Model
In this study, the transformer model, a deep learning neural network model developed primarily for the natural language processing and vision tasks, was adapted for a time-series analysis of motion signals.
IMUGPT 2.0: Language-Based Cross Modality Transfer for Sensor-Based Human Activity Recognition
With the emergence of generative AI models such as large language models (LLMs) and text-driven motion synthesis models, language has become a promising source data modality as well as shown in proof of concepts such as IMUGPT.
SALIENCE: An Unsupervised User Adaptation Model for Multiple Wearable Sensors Based Human Activity Recognition
In order to address the challenge that the transferabilities of different sensors are different, we propose SALIENCE (unsupervised user adaptation model for multiple wearable sensors based human activity recognition) model.
Attention-Based Deep Learning Framework for Human Activity Recognition with User Adaptation
We propose a simple and effective transfer-learning based strategy to adapt a model to a specific user, providing an average increment of $6\%$ on the F1 score on the predictions for that user.
Feature engineering workflow for activity recognition from synchronized inertial measurement units
The ubiquitous availability of wearable sensors is responsible for driving the Internet-of-Things but is also making an impact on sport sciences and precision medicine.
HARDVS: Revisiting Human Activity Recognition with Dynamic Vision Sensors
The main streams of human activity recognition (HAR) algorithms are developed based on RGB cameras which are suffered from illumination, fast motion, privacy-preserving, and large energy consumption.
Out-of-Distribution Representation Learning for Time Series Classification
Time series classification is an important problem in real world.
Deep Learning for Sensor-based Activity Recognition: A Survey
This paper surveys the recent advance of deep learning based sensor-based activity recognition.
