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Handling missing data in rest-activity time series measured by actimetry

Research output: Contribution to journalArticlepeer-review

André Comiran Tonon, Luísa K. Pilz, Guilherme Rodriguez Amando, Débora Barroggi Constantino, Rogério Boff Borges, Arthur Caye, Fernanda Rohrsetzer, Laila Souza, Helen Fisher, Brandon A Kohrt, Valeria Mondelli, Christian Kieling, Marco Idiart, Antoni Diez-Noguera, Maria Paz Hidalgo

Original languageEnglish
Pages (from-to)964-975
Number of pages12
JournalChronobiology international
Issue number7
Early online date30 Mar 2022
Accepted/In press6 Mar 2022
E-pub ahead of print30 Mar 2022

Bibliographical note

Funding Information: Dr Andre received financial support by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), and Dr Idiart and Dr Hidalgo from Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq). Dr Kieling is a CNPq researcher and a UK Academy of Medical Sciences Newton Advanced Fellow. Dr Mondelli is supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London and has received research funding from Johnson & Johnson, a pharmaceutical company interested in the development of anti-inflammatory strategies for depression, but the research described in this paper is unrelated to this funding. Dr Fisher is part supported by the Economic and Social Research Council (ESRC) Centre for Society and Mental Health at King’s College London [ES/S012567/1]. The IDEA project is funded by an MQ Brighter Futures grant [MQBF/1 IDEA]. Additional support was provided by the UK Medical Research Council [MC_PC_MR/R019460/1] and the Academy of Medical Sciences [GCRFNG\100281] under the Global Challenges Research Fund. BAK received support from the US National Institute of Mental Health [K01MH104310, R21MH111280].We are also grateful to all members of the IDEA team for their dedication and hard work. We are grateful to the team of Laboratório de Cronobiologia e Sono HCPA/UFRGS, especially Ana Abreu, Melissa de Oliveira and Nicóli Xavier, for the insightful input to this project and to other projects in this research line. Publisher Copyright: © 2022 Taylor & Francis Group, LLC.


King's Authors


A handling procedure of off-wrist episodes in actimetry time series of motor activity is presented using two records (regular vs. irregular sleep-wake cycle and daytime activity) of 14 consecutive days sampled in 1-minute epochs. We generated single missing value (NA) intervals of 1 h, 2 h, 4 h, 6 h, 12 h, and 24 h as well as random NA episodes following probabilistic rules to simulate real-life off-wrist episodes. Then, we replaced these episodes with “zeroes” (i.e., the default of immobility records), mean or median of the remaining 13 days corresponding to the missing bins. Single missing episodes of up to 12 h resulted in less than 5% variation from the original values. The irregular series showed higher variability in acrophase, MESOR, L5, M10 and RA compared to the regular series. Random missing allocation simulating real-life off-wrist episodes resulted in significant changes in most parameters, and the imputation of zeroes significantly increased the variance; however, replacing NA with mean or median resulted in patterns similar to those of NA. We recommend replacing ‘zeroes’ with NA whenever possible, given the risk of inflating invariance using zeroes. If the parameters cannot be computed in the presence of NA, we recommend using the weekly mean of corresponding timepoints.

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