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Citation

BibTex format

@article{Palermo:2023:10.1038/s41597-023-02519-y,
author = {Palermo, F and Chen, Y and Capstick, A and Fletcher-Lloyd, N and Walsh, C and Kouchaki, S and Jessica, T and Balazikova, O and Soreq, E and Scott, G and Rostill, H and Nilforooshan, R and Barnaghi, P},
doi = {10.1038/s41597-023-02519-y},
journal = {Scientific Data},
pages = {1--10},
title = {TIHM: an open dataset for remote healthcare monitoring in dementia},
url = {http://dx.doi.org/10.1038/s41597-023-02519-y},
volume = {10},
year = {2023}
}

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TY  - JOUR
AB  - Dementia is a progressive condition that affects cognitive and functional abilities. There is a need for reliable and continuous health monitoring of People Living with Dementia (PLWD) to improve their quality of life and support their independent living. Healthcare services often focus on addressing and treating already established health conditions that affect PLWD. Managing these conditions continuously can inform better decision-making earlier for higher-quality care management for PLWD. The Technology Integrated Health Management (TIHM) project developed a new digital platform to routinely collect longitudinal, observational, and measurement data, within the home and apply machine learning and analytical models for the detection and prediction of adverse health events affecting the well-being of PLWD. This work describes the TIHM dataset collected during the second phase (i.e., feasibility study) of the TIHM project. The data was collected from homes of 56 PLWD and associated with events and clinical observations (daily activity, physiological monitoring, and labels for health-related conditions). The study recorded an average of 50 days of data per participant, totalling 2803 days.
AU  - Palermo,F
AU  - Chen,Y
AU  - Capstick,A
AU  - Fletcher-Lloyd,N
AU  - Walsh,C
AU  - Kouchaki,S
AU  - Jessica,T
AU  - Balazikova,O
AU  - Soreq,E
AU  - Scott,G
AU  - Rostill,H
AU  - Nilforooshan,R
AU  - Barnaghi,P
DO  - 10.1038/s41597-023-02519-y
EP  - 10
PY  - 2023///
SN  - 2052-4463
SP  - 1
TI  - TIHM: an open dataset for remote healthcare monitoring in dementia
T2  - Scientific Data
UR  - http://dx.doi.org/10.1038/s41597-023-02519-y
UR  - https://www.nature.com/articles/s41597-023-02519-y
VL  - 10
ER  -

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Awards

Finalist: Best Paper - IEEE Transactions on Mechatronics (awarded June 2021)
Finalist: IEEE Transactions on Mechatronics; 1 of 5 finalists for Best Paper in Journal
Winner: UK Institute of Mechanical Engineers (IMECHE) Healthcare Technologies Early Career Award (awarded June 2021): Awarded to Maria Lima (UKDRI CR&T PhD candidate)
Winner: Sony Start-up Acceleration Program (awarded May 2021): Spinout company Serg Tech awarded (1 of 4 companies in all of Europe) a place in Sony corporation start-up boot camp
“An Extended Complementary Filter for Full-Body MARG Orientation Estimation” (CR&T authors: S Wilson, R Vaidyanathan)

Established in 2017 by its principal funder the Medical 91��ɫ Council, in partnership with Alzheimer's Society and Alzheimer’s 91��ɫ UK, The (UK DRI) is the UK’s leading biomedical research institute dedicated to neurodegenerative diseases.