Investigating the Effects of Applying Different Actigraphy Processing Approaches to Examine the Sleep Data of Patients With Neuropathic Pain

in Journal for the Measurement of Physical Behaviour

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Hannah J. Coyle-AsbilDepartment of Human Health and Nutritional Sciences, University of Guelph, Guelph, Canada
Department of Anesthesiology and Pain Management, Women’s College Hospital, Toronto, Canada
Department of Anesthesiology and Pain Management, University Health Network, University of Toronto, Toronto, Canada

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Anuj BhatiaDepartment of Anesthesiology and Pain Management, Women’s College Hospital, Toronto, Canada
Department of Anesthesiology and Pain Management, University Health Network, University of Toronto, Toronto, Canada
Department of Anesthesia and Pain Medicine, University of Toronto, Toronto, Canada

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Andrew LimDepartment of Anesthesia and Pain Medicine, University of Toronto, Toronto, Canada
Department of Neurology, Sunnybrook Health Sciences Center, Toronto, Canada

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Mandeep SinghDepartment of Anesthesiology and Pain Management, Women’s College Hospital, Toronto, Canada
Department of Anesthesiology and Pain Management, University Health Network, University of Toronto, Toronto, Canada
Department of Anesthesia and Pain Medicine, University of Toronto, Toronto, Canada

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DOI:
https://doi.org/10.1123/jmpb.2022-0017
Keywords:
spinal cord stimulation; accelerometers; clinical applications; health outcomes
First Published Online:
28 Sep 2022
In Print:
Volume 5: Issue 4
Page Range:
288–293
Restricted access

Individuals suffering from neuropathic pain commonly report issues associated with sleep. To measure sleep in this population, researchers have used actigraphy. Historically, actigraphy data have been analyzed in the form of counts; however, due to the proprietary nature, many opt to quantify data in its raw form. Various processing techniques exist to accomplish this; however, it remains unclear how they compare to one another. This study sought to compare sleep measures derived using the GGIR R package versus the GENEActiv (GA) R Markdown tool in a neuropathic pain population. It was hypothesized that the processing techniques would yield significantly different sleep outcomes. One hundred and twelve individuals (mean age = 52.72 ± 13.01 years; 60 M) with neuropathic pain in their back and/or lower limbs were included. While simultaneously undergoing spinal cord stimulation, actigraphy devices were worn on the wrist for a minimum of 7 days (GA; 50 Hz). Upon completing the protocol, sleep outcome measures were calculated using (a) the GGIR R package and (b) the GA R Markdown tool. To compare these algorithms, paired-samples t tests and Bland–Altman plots were used to compare the total sleep time, sleep efficiency, wake after sleep onset, sleep onset time, and rise times. According to the paired-samples t test, the GA R Markdown yielded lower total sleep time and sleep efficiency and a greater wake after sleep onset, compared with the GGIR package. Furthermore, later sleep onset times and earlier rise times were reported by the GGIR package compared with the GA R Markdown.

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