IMU-based monitoring for assistive diagnosis and management of IoHT: a review
With the rapid development of Internet of Things (IoT) technologies, traditional disease
diagnoses carried out in medical institutions can now be performed remotely at home or …
diagnoses carried out in medical institutions can now be performed remotely at home or …
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 …
Pi-net: A deep learning approach to extract topological persistence images
Topological features such as persistence diagrams and their functional approximations like
persistence images (PIs) have been showing substantial promise for machine learning and …
persistence images (PIs) have been showing substantial promise for machine learning and …
The role of heart-rate variability parameters in activity recognition and energy-expenditure estimation using wearable sensors
Human-activity recognition (HAR) and energy-expenditure (EE) estimation are major
functions in the mobile healthcare system. Both functions have been investigated for a long …
functions in the mobile healthcare system. Both functions have been investigated for a long …
Identifying free-living physical activities using lab-based models with wearable accelerometers
The purpose of this study was to classify, and model various physical activities performed by
a diverse group of participants in a supervised lab-based protocol and utilize the model to …
a diverse group of participants in a supervised lab-based protocol and utilize the model to …
Unsupervised pre-trained models from healthy ADLs improve Parkinson's disease classification of gait patterns
Application and use of deep learning algorithms for different healthcare applications is
gaining interest at a steady pace. However, use of such algorithms can prove to be …
gaining interest at a steady pace. However, use of such algorithms can prove to be …
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 …
Topological knowledge distillation for wearable sensor data
Converting wearable sensor data to actionable health insights has witnessed large interest
in recent years. Deep learning methods have been utilized in and have achieved a lot of …
in recent years. Deep learning methods have been utilized in and have achieved a lot of …
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 …