In the domain of physical rehabilitation, the progress in machine learning and the availability
of cost-effective motion capture technologies have paved the way for innovative systems …

Access to healthcare, including physiotherapy, is increasingly occurring through virtual
formats. At-home adherence to physical therapy programs is often poor and few tools exist to …

Abstract Machine learning has emerged as a promising approach to enhance rehabilitation
therapy monitoring and evaluation, providing personalized insights. However, the scarcity of …

As is the case with any very complex and interactive software, many video games are
released with various minor or major issues that can potentially affect the user experience …

As more apps embrace AI, it is becoming increasingly common that multiple Deep Neural
Networks (DNN)-powered apps may run at the same time on a mobile device. This paper …

Abstract Low-power Machine Learning (ML) technologies that process data locally on
consumer-level hardware are well suited for interactive applications, however, their potential …

We present MovePose, an optimized lightweight convolutional neural network designed
specifically for real-time body pose estimation on CPU-based mobile devices. The current …

Gait abnormalities can be related to locomotion injuries or to various musculoskeletal and
neurological pathologies. In this paper an automatic method for gait analysis and evaluation …

The falling-and sliding-down (fall) accidents among the elderly are a major concern due to
the potential to cause significant functional damage. This demands immediate medical care …

This paper contributes to the body of work examining how designers can be supported in
integrating machine learning (ML) capabilities into their designs for novel applications and …