Abstract
Radar sensors are an emerging technology in the context of non-contact monitoring of vulnerable individuals. Radar-based solutions ensure end-user privacy, whilst providing medical professionals and caregivers with key information concerning the subject's well-being. This thesis proposes novel methods for the classification of sequential human activities using a network of radar sensors. Accurate classification of Activities of Daily Life (ADL) can enable for instance the detection of falls and wandering amongst elderly individuals, and can be employed for the recognition of aggressive or otherwise anomalous behaviour for those receiving mental health care.
| Original language | English |
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| Qualification | Doctor of Philosophy |
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| Supervisors/Advisors |
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| Award date | 26 Mar 2025 |
| Print ISBNs | 978-94-6384-756-8 |
| Electronic ISBNs | 978-94-6518-033-5 |
| DOIs | |
| Publication status | Published - 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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