Sleep monitoring plays a crucial role in maintaining good health, with sleep staging serving as an essential metric in the monitoring process. Traditional methods, utilizing medical sensors like EEG and ECG, can be effective but often present challenges ...

Sensor-based HAR models face challenges in cross-subject generalization due to the complexities of data collection and annotation, impacting the size and representativeness of datasets. While data augmentation has been successfully employed in domains ...

Major Depressive Disorder (MDD) and Generalized Anxiety Disorder (GAD) are both heterogeneous in their clinical presentations, manifesting with unique symptom profiles. Despite this, prior digital phenotype research has primarily focused on disorder-...

Smart speaker voice assistants (VAs) such as Amazon Echo and Google Home have been widely adopted due to their seamless integration with smart home devices and the Internet of Things (IoT) technologies. These VA services raise privacy concerns, ...

The development of a machine-learning-based human activity recognition (HAR) system using body-worn sensors is mainly composed of three phases: data collection, model training, and evaluation. During data collection, the HAR developer collects labeled ...

The growing prevalence of depression and suicidal ideation among college students further exacerbated by the Coronavirus pandemic is alarming, highlighting the need for universal mental illness screening technology. With traditional screening ...

The rates of mental illness, especially anxiety and depression, have increased greatly since the start of the COVID-19 pandemic. Traditional mental illness screening instruments are too cumbersome and biased to screen an entire population. In contrast, ...

This study presents a new neural network model for recognizing manual works using body-worn accelerometers in industrial settings, named Lightweight Ordered-work Segmentation Network (LOS-Net). In industrial domains, a human worker typically repetitively ...

Wearables are fundamental to improving our understanding of human activities, especially for an increasing number of healthcare applications from rehabilitation to fine-grained gait analysis. Although our collective know-how to solve Human Activity ...

This paper proposes and evaluates the use of image classification for detailed, full-body human-robot tactile interaction. A camera positioned below a translucent robot skin captures shadows generated from human touch and infers social gestures from the ...

Recent work has shown the feasibility of producing knitted capacitive touch sensors through digital fabrication with little human intervention in the textile production process. Such sensors can be designed and manufactured at scale and require only two ...

The lack of large-scale, labeled data sets impedes progress in developing robust and generalized predictive models for on-body sensor-based human activity recognition (HAR). Labeled data in human activity recognition is scarce and hard to come by, as ...

Distinguishing identities is useful for several applications such as automated grocery or personalized recommendations. Unfortunately, several recent proposals for identification systems are evaluated using poor recruitment practices. We discovered that ...

Many mobile applications such as Strava or Mapmyride allow cyclists to collect detailed GPS traces of their trips for health or route sharing purposes. However, cycling GPS traces also have a lot of potential from an urban planning perspective. In this ...

In this paper, we propose a method for detecting conversing groups. More specifically, we detect pairwise F-formation membership using a single worn accelerometer. We focus on crowded real life scenarios, specifically mingling events, where groups of ...

Event detection of indoor objects, including doors, has a wide variety of applications, including intruder detection, HVAC control, and surveillance of independently living elderly people. Hence, this has been the focus of multiple research projects in ...

Recent years have seen the increasing need of location awareness by mobile applications. This paper presents a room-level indoor localization approach based on the measured room's echos in response to a two-millisecond single-tone inaudible chirp emitted ...

Recent advances in wearable camera technology and computer vision algorithms have greatly enhanced the automatic capture and recognition of human activities in real-world settings. While the appeal and utility of wearable camera devices for human-...

Detecting the events of indoor everyday objects such as door or window open/close events has been actively studied to implement such applications as intrusion detection, adaptive HVAC control, and monitoring an independently living elderly person. This ...

Quality assessment in cricket is a complex task that is performed by understanding the combination of individual activities a player is able to perform and by assessing how well these activities are performed. We present a framework for inexpensive and ...