Activity recognition is a popular research area with a number of applications, particularly in
the smart home environment. The unique features of smart home sensors have challenged …

Recently, deep learning (DL) methods have been introduced very successfully into human
activity recognition (HAR) scenarios in ubiquitous and wearable computing. Especially the …

Research on sensor-based activity recognition has, recently, made significant progress and
is attracting growing attention in a number of disciplines and application domains. However …

This paper introduces a publicly available dataset of complex activities that involve
manipulative gestures. The dataset captures people preparing mixed salads and contains …

We describe the development, application and evaluation of a design method tailored for
working with people with mild to moderate dementia. Our experiences with the approach …

With the global population aging, the demand for technologies facilitating independent
living, especially for those with cognitive impairments, is increasing. This paper addresses …

Real-world deployments of accelerometer-based human activity recognition systems need
to be carefully configured regarding the sampling rate used for measuring acceleration …

Previous research on interlanguage pragmatics revealed that, under implicit pragmatic
instruction, some learners noticed the target pragmalinguistic features, whereas others …

Activity models play a critical role for activity recognition and assistance in ambient assisted
living. Existing approaches to activity modeling suffer from a number of problems, eg, cold …

We propose a sparse-coding framework for activity recognition in ubiquitous and mobile
computing that alleviates two fundamental problems of current supervised learning …