Point Transformer-Based Human Activity Recognition Using High-Dimensional Radar Point Clouds

Radar-based Human Activity Recognition(HAR) is considered by using snapshots of point clouds. Such point cloudsinterpret 2D images generated by an mm-wave FMCW MIMO radar enriched byincluding Doppler and temporal information. We use the similarity between suchradar data representation and the core of the self-attention concept inartificial...

Radar Sensing in Healthcare: Challenges and Achievements in Human Activity Classification & Vital Signs Monitoring

Driven by its contactless sensing capabilities and the lack of optical images being recorded, radar technology has been recently investigated in the context of human healthcare. This includes a broad range of applications, such as human activity classification, fall detection, gait and mobility analysis, and monitoring of vital signs such as...

Continuous People Crowd Monitoring defined as a Regression Problem using Radar Networks

Radar-based human activity recognition in crowded environments using regression approaches is addressed. Whereas previous research has focused on single activities and subjects, the problem of continuous activity recognition involving up to five individuals moving in arbitrary directions in an indoor area is introduced. To treat the problem, a...

Exploiting Radar Data Domains for Classification with Spatially Distributed Nodes

Recognition of continuous human activities is investigated in unconstrained movement directions using multiple spatially distributed radar nodes, where activities can occur at unfavourable aspect angles or occluded perspectives when using a single node. Furthermore, such networks are favourable not only for the aforementioned aim, but also for...

Distributed Radar-based Human Activity Recognition using Vision Transformer and CNNs

The feasibility of classifying human activities measured by a distributed ultra-wideband (UWB) radar system using Range-Doppler (RD) images as the input to classifiers is investigated. Kinematic characteristics of different human activities are expected to be captured in high-resolution range-Doppler images measured by UWB radars. To construct...

Radar-based Human Activities Classification with Complex-valued Neural Networks

Human activities classification in assisted living is one of the emerging applications of radar. The conventional analysis considers micro-Doppler signatures as the chosen input for feature extraction or deep learning classification algorithms, or, less frequently, other radar data formats such as the range-time, the range-Doppler, or the...

Evaluation Metrics for Continuous Human Activity Classification Using Distributed Radar Networks

Continuous Human Activity Recognition (HAR) in arbitrary directions is investigated using 5 spatially distributed pulsed Ultra-Wideband (UWB) radars. Such activities performed in arbitrary and unconstrained trajectories render a more natural occurrence of Activities of Daily Living (ADL) to be recognized. An innovative signal level fusion method...

Continuous human activity recognition for arbitrary directions with distributed radars

Continuous Activities of Daily Living (ADL) recognition in an arbitrary movement direction using five distributed pulsed Ultra-Wideband (UWB) radars in a coordinated network is proposed. Classification approaches in unconstrained activity trajectories that render a more natural occurrence for Human Activity Recognition (HAR) are investigated....

Derivative Target Line (DTL) for Continuous Human Activity Detection and Recognition

In this paper, we investigate the classification of Activities of Daily Living (ADL) by using a pulsed ultra-wideband radar. Specifically, we focus on contiguous activities that can be inseparable in time and share a common transition, such as walking and falling. The range-time data domain is deliberately exploited to determine transitions from...