ArticleSensors (Basel, Switzerland)2022
Privacy-Preserving Human Action Recognition with a Many-Objective Evolutionary Algorithm.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- An Interdisciplinary Overview on Ambient Assisted Living Systems for Health Monitoring at Home: Trade-Offs and Challenges.Sensors (Basel, Switzerland) · 2025Review
- Human Action Recognition in Smart Living Services and Applications: Context Awareness, Data Availability, Personalization, and Privacy.Sensors (Basel, Switzerland) · 2023Review
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Wrist-worn devices equipped with accelerometers constitute a non-intrusive way to achieve active and assisted living (AAL) goals, such as automatic journaling for self-reflection, i.e., lifelogging, as well as to provide other services, such as general health and wellbeing monitoring, personal autonomy assessment, among others. Human action recognition (HAR), and in particular, the recognition of activities of daily living (ADLs), can be used for these types of assessment or journaling. In this paper, a many-objective evolutionary algorithm (MaOEA) is used in order to maximise action recognition from individuals while concealing (minimising recognition of) gender and age. To validate the proposed method, the PAAL accelerometer signal ADL dataset (v2.0) is used, which includes data from 52 participants (26 men and 26 women) and 24 activity class labels. The results show a drop in gender and age recognition to 58% (from 89%, a 31% drop), and to 39% (from 83%, a 44% drop), respectively; while action recognition stays closer to the initial value of 68% (from: 87%, i.e., 19% down).
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.