We have located links that may give you full text access.
JOURNAL ARTICLE
RESEARCH SUPPORT, NON-U.S. GOV'T
The Effect of Personalization on Smartphone-Based Fall Detectors.
Sensors 2016
The risk of falling is high among different groups of people, such as older people, individuals with Parkinson's disease or patients in neuro-rehabilitation units. Developing robust fall detectors is important for acting promptly in case of a fall. Therefore, in this study we propose to personalize smartphone-based detectors to boost their performance as compared to a non-personalized system. Four algorithms were investigated using a public dataset: three novelty detection algorithms--Nearest Neighbor (NN), Local Outlier Factor (LOF) and One-Class Support Vector Machine (OneClass-SVM)--and a traditional supervised algorithm, Support Vector Machine (SVM). The effect of personalization was studied for each subject by considering two different training conditions: data coming only from that subject or data coming from the remaining subjects. The area under the receiver operating characteristic curve (AUC) was selected as the primary figure of merit. The results show that there is a general trend towards the increase in performance by personalizing the detector, but the effect depends on the individual being considered. A personalized NN can reach the performance of a non-personalized SVM (average AUC of 0.9861 and 0.9795, respectively), which is remarkable since NN only uses activities of daily living for training.
Full text links
Trending Papers
A Personalized Approach to the Management of Congestion in Acute Heart Failure.Heart International 2023
Potential Mechanisms of the Protective Effects of the Cardiometabolic Drugs Type-2 Sodium-Glucose Transporter Inhibitors and Glucagon-like Peptide-1 Receptor Agonists in Heart Failure.International Journal of Molecular Sciences 2024 Februrary 21
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app
All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.
By using this service, you agree to our terms of use and privacy policy.
Your Privacy Choices
You can now claim free CME credits for this literature searchClaim now
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app