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We present MoCaPose, a novel wearable motion capturing (MoCap) approach to continuously track the wearer's upper body's dynamic poses through multi-channel capacitive sensing integrated in fashionable, loose-fitting jackets. Unlike conventional wearable ...

The physical and physiological development of infants and toddlers requires the proper amount of macronutrient intake, making it an essential problem to estimate the macronutrient in baby food. Nevertheless, existing solutions are either too expensive ...

Many patients with neurological disorders, such as Ataxia, do not have easy access to neurologists, -especially those living in remote localities and developing/underdeveloped countries. Ataxia is a degenerative disease of the nervous system that ...

Activity recognition using video data is widely adopted for elder care, monitoring for safety and security, and home automation. Unfortunately, using video data as the basis for activity recognition can be brittle, since models trained on video are ...

Imagine a near-future smart home. Home-embedded visual AI sensors continuously monitor the resident, inferring her activities and internal states that enable higher-level services. Here, as home-embedded sensors passively monitor a free person, good ...

End-to-end deep learning models are increasingly applied to safety-critical human activity recognition (HAR) applications, e.g., healthcare monitoring and smart home control, to reduce developer burden and increase the performance and robustness of ...

In clinical settings, most automatic recognition systems use visual or sensory data to recognize activities. These systems cannot recognize activities that rely on verbal assessment, lack visual cues, or do not use medical devices. We examined speech-...

Physical therapy (PT) is crucial for patients to restore and maintain mobility, function, and well-being. Many on-site activities and body exercises are performed under the supervision of therapists or clinicians. However, the postures of some exercises ...

Freehand interaction enhances user experience, allowing one to use bare hands to manipulate virtual objects in AR. Yet, it remains challenging to accurately and efficiently detect contacts between real hand and virtual object, due to the imprecise ...

3D Point Cloud Data (PCD) has been used in many research and commercial applications widely, such as autonomous driving, robotics, and VR/AR. But existing PCD generation systems based on RGB-D and LiDARs require robust lighting and an unobstructed field ...

Federated Learning (FL) allows several data owners to train a joint model without sharing their training data. Such a paradigm is useful for better privacy in many ubiquitous computing systems. However, FL is vulnerable to poisoning attacks, where ...

The availability of commercial wearable trackers equipped with features to monitor sleep duration and quality has enabled more useful sleep health monitoring applications and analyses. However, much research has reported the challenge of long-term user ...

Wearable, embedded, and IoT devices are a centrepiece of many ubiquitous computing applications, such as fitness tracking, health monitoring, home security and voice assistants. By gathering user data through a variety of sensors and leveraging machine ...

Driver emotions play a vital role in driving safety and performance. Consequently, regulating driver emotions through empathic interfaces have been investigated thoroughly. However, the prerequisite - driver emotion sensing - is a challenging endeavor: ...

Airlines overestimate the weight of their passengers by simply assigning a constant weight for everyone, causing each plane to burn more fuel than needed to carry the extra weight. Accurately estimating the passenger weights is a difficult problem for ...

Proper indoor ventilation through buildings' heating, ventilation, and air conditioning (HVAC) systems has become an increasing public health concern that significantly impacts individuals' health and safety at home, work, and school. While much work ...

Smartwatches or fitness trackers have garnered a lot of popularity as potential health tracking devices due to their affordable and longitudinal monitoring capabilities. To further widen their health tracking capabilities, in recent years researchers ...

A major bottleneck in training robust Human-Activity Recognition models (HAR) is the need for large-scale labeled sensor datasets. Because labeling large amounts of sensor data is an expensive task, unsupervised and semi-supervised learning techniques ...

Touchscreens are the primary input devices for smartphones and tablets. Although widely used, the output of touchscreen controllers is still limited to the two-dimensional position of the contacting finger. Finger angle (or orientation) estimation from ...

Trip purpose - i.e., why people travel - is an important yet challenging research topic in travel behavior analysis. Generally, the key to this problem is understanding the activity semantics from trip contexts. However, most existing methods rely on ...