Human activity recognition using inertial, physiological and environmental sensors: A comprehensive survey
In the last decade, Human Activity Recognition (HAR) has become a vibrant research area,
especially due to the spread of electronic devices such as smartphones, smartwatches and …
especially due to the spread of electronic devices such as smartphones, smartwatches and …
Topological persistence guided knowledge distillation for wearable sensor data
Deep learning methods have achieved a lot of success in various applications involving
converting wearable sensor data to actionable health insights. A common application areas …
converting wearable sensor data to actionable health insights. A common application areas …
Functional data analysis approach for mapping change in time series: A case study using bicycle ridership patterns
Monitoring change is an important aspect of understanding variations in spatial–temporal
processes. Recently,'big data'on mobility, which are detailed across space and time, have …
processes. Recently,'big data'on mobility, which are detailed across space and time, have …
Step by step towards effective human activity recognition: A balance between energy consumption and latency in health and wellbeing applications
E Cero Dinarević, J Baraković Husić, S Baraković - Sensors, 2019 - mdpi.com
Human activity recognition (HAR) is a classification process that is used for recognizing
human motions. A comprehensive review of currently considered approaches in each stage …
human motions. A comprehensive review of currently considered approaches in each stage …
Constrained Adaptive Distillation Based on Topological Persistence for Wearable Sensor Data
Wearable sensor data analysis with persistence features generated by topological data
analysis (TDA) has achieved great success in various applications, and however, it suffers …
analysis (TDA) has achieved great success in various applications, and however, it suffers …
Uncertainty-Aware Topological Persistence Guided Knowledge Distillation on Wearable Sensor Data
In applications involving analysis of wearable sensor data, machine learning techniques that
use features from topological data analysis (TDA) have demonstrated remarkable …
use features from topological data analysis (TDA) have demonstrated remarkable …
Role of data augmentation strategies in knowledge distillation for wearable sensor data
Deep neural networks are parametrized by several thousands or millions of parameters and
have shown tremendous success in many classification problems. However, the large …
have shown tremendous success in many classification problems. However, the large …
[PDF][PDF] Robustness of topological persistence in knowledge distillation for wearable sensor data
Topological data analysis (TDA) has shown great success in various applications involving
wearable sensor data. However, there are difficulties in leveraging topological features in …
wearable sensor data. However, there are difficulties in leveraging topological features in …
Role of Mixup in Topological Persistence Based Knowledge Distillation for Wearable Sensor Data
The analysis of wearable sensor data has enabled many successes in several applications.
To represent the high-sampling rate time-series with sufficient detail, the use of topological …
To represent the high-sampling rate time-series with sufficient detail, the use of topological …
Shape Analysis for Pediatric Upper Body Motor Function Assessment
Neuromuscular disorders, such as (SMA) and Duchenne Muscular Dystrophy (DMD), cause
progressive muscular degeneration and loss of motor function for 1 in 6,000 children …
progressive muscular degeneration and loss of motor function for 1 in 6,000 children …