Feasibility of a simple method for identifying sleep periods from Holter recordings

C. Williams; Phyllis K. Stein; P. P. Domitrovich; T. R. Taylor

Feasibility of a simple method for identifying sleep periods from Holter recordings

C. Williams, Phyllis K. Stein, P. P. Domitrovich, T. R. Taylor

Research output: Contribution to journal › Conference article › peer-review

Abstract

To determine whether sleep periods can be identified from Holter-derived data using a combination of hourly average HR patterns and hourly spectral plots, Holter data from N=77 randomly-selected subjects with self-reported bed:wake (B:W) times were examined. N=50 were patients with a recent MI (C), 12 were younger subjects from a Holter quality validation study (Y), and 15 were subjects>65 years old from the Cardiovascular Health Study (O). N=18 (C) were excluded for a combination of abnormal circadian rhythm and abnormal HRV plots. The accuracy of hourly HR + HRV patterns to identify bedtime ± 1hr was: 100% (O), 84% (C), and 100% (Y). Hourly HR+HRV patterns identified wake-times ± 1hr 100% of the time for (O), 91% for (C) and 100% (Y). Identification of sleep periods from Holter data appears feasible in different groups using a simple algorithm. This method could permit detailed study of sleep periods in Holter cohorts where diaries are unavailable.

Original language	English
Pages (from-to)	533-536
Number of pages	4
Journal	Computers in Cardiology
Volume	29
State	Published - Dec 1 2002
Event	Computers in Cardiology 2002 - Memphis, TN, United States Duration: Sep 22 2002 → Sep 25 2002

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@article{b2cc5b66ba6d4e628ccf8848a6c1977b,

title = "Feasibility of a simple method for identifying sleep periods from Holter recordings",

abstract = "To determine whether sleep periods can be identified from Holter-derived data using a combination of hourly average HR patterns and hourly spectral plots, Holter data from N=77 randomly-selected subjects with self-reported bed:wake (B:W) times were examined. N=50 were patients with a recent MI (C), 12 were younger subjects from a Holter quality validation study (Y), and 15 were subjects>65 years old from the Cardiovascular Health Study (O). N=18 (C) were excluded for a combination of abnormal circadian rhythm and abnormal HRV plots. The accuracy of hourly HR + HRV patterns to identify bedtime ± 1hr was: 100% (O), 84% (C), and 100% (Y). Hourly HR+HRV patterns identified wake-times ± 1hr 100% of the time for (O), 91% for (C) and 100% (Y). Identification of sleep periods from Holter data appears feasible in different groups using a simple algorithm. This method could permit detailed study of sleep periods in Holter cohorts where diaries are unavailable.",

author = "C. Williams and Stein, {Phyllis K.} and Domitrovich, {P. P.} and Taylor, {T. R.}",

year = "2002",

month = dec,

day = "1",

language = "English",

volume = "29",

pages = "533--536",

journal = "Computers in Cardiology",

issn = "0276-6574",

note = "null ; Conference date: 22-09-2002 Through 25-09-2002",

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TY - JOUR

T1 - Feasibility of a simple method for identifying sleep periods from Holter recordings

AU - Williams, C.

AU - Stein, Phyllis K.

AU - Domitrovich, P. P.

AU - Taylor, T. R.

PY - 2002/12/1

Y1 - 2002/12/1

N2 - To determine whether sleep periods can be identified from Holter-derived data using a combination of hourly average HR patterns and hourly spectral plots, Holter data from N=77 randomly-selected subjects with self-reported bed:wake (B:W) times were examined. N=50 were patients with a recent MI (C), 12 were younger subjects from a Holter quality validation study (Y), and 15 were subjects>65 years old from the Cardiovascular Health Study (O). N=18 (C) were excluded for a combination of abnormal circadian rhythm and abnormal HRV plots. The accuracy of hourly HR + HRV patterns to identify bedtime ± 1hr was: 100% (O), 84% (C), and 100% (Y). Hourly HR+HRV patterns identified wake-times ± 1hr 100% of the time for (O), 91% for (C) and 100% (Y). Identification of sleep periods from Holter data appears feasible in different groups using a simple algorithm. This method could permit detailed study of sleep periods in Holter cohorts where diaries are unavailable.

AB - To determine whether sleep periods can be identified from Holter-derived data using a combination of hourly average HR patterns and hourly spectral plots, Holter data from N=77 randomly-selected subjects with self-reported bed:wake (B:W) times were examined. N=50 were patients with a recent MI (C), 12 were younger subjects from a Holter quality validation study (Y), and 15 were subjects>65 years old from the Cardiovascular Health Study (O). N=18 (C) were excluded for a combination of abnormal circadian rhythm and abnormal HRV plots. The accuracy of hourly HR + HRV patterns to identify bedtime ± 1hr was: 100% (O), 84% (C), and 100% (Y). Hourly HR+HRV patterns identified wake-times ± 1hr 100% of the time for (O), 91% for (C) and 100% (Y). Identification of sleep periods from Holter data appears feasible in different groups using a simple algorithm. This method could permit detailed study of sleep periods in Holter cohorts where diaries are unavailable.

UR - http://www.scopus.com/inward/record.url?scp=0036955627&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:0036955627

VL - 29

SP - 533

EP - 536

JO - Computers in Cardiology

JF - Computers in Cardiology

SN - 0276-6574

Y2 - 22 September 2002 through 25 September 2002

ER -