toward a taxonomy of autonomic sleep patterns with electrodermal activity akane sano and rosalind w....

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Toward a Taxonomy of Autonomic Sleep Patterns with Electrodermal Activity Akane Sano and Rosalind W. Picard, Massachusetts Institute of Technology Media Lab Affective Computing Group [email protected]

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Page 1: Toward a Taxonomy of Autonomic Sleep Patterns with Electrodermal Activity Akane Sano and Rosalind W. Picard, Massachusetts Institute of Technology Media

Toward a Taxonomy of Autonomic Sleep Patterns with Electrodermal Activity

Akane Sano and Rosalind W. Picard, Massachusetts Institute of Technology

Media LabAffective Computing Group

[email protected]

Page 2: Toward a Taxonomy of Autonomic Sleep Patterns with Electrodermal Activity Akane Sano and Rosalind W. Picard, Massachusetts Institute of Technology Media

What is Electrodermal Activity?•Electrical measures of sweat gland activity

• Index of sympathetic nervous activation

•Classically, has been measured with wired and gelled electrodes on the skin

•Our research group developed a dry electrode, wearable sensor for long-term ambulatory measurement

Page 3: Toward a Taxonomy of Autonomic Sleep Patterns with Electrodermal Activity Akane Sano and Rosalind W. Picard, Massachusetts Institute of Technology Media

Electrodermal Activity (EDA) during sleepQ:Sympathetic nervous activity goes up

during a day and goes down and get silent during sleep?

A: No!!!

High frequency “storm” patterns during sleep

Why these storm patterns happen?

Page 4: Toward a Taxonomy of Autonomic Sleep Patterns with Electrodermal Activity Akane Sano and Rosalind W. Picard, Massachusetts Institute of Technology Media

Measurement of SleepPolysomnography (PSG)

+ measures EEG and more, provides 30 s epochs labeled as: Wake, NonREM (stage 1-3), and REM

- expensive and obtrusive

Actigraphy

+ less invasive than PSG, low cost

- only measures movement

Our EDA sensor

+ comfortable, same or lower cost than actigraphy

+ measures EDA, skin temperature and actigraphy

-+ measures different patterns than traditional

Page 5: Toward a Taxonomy of Autonomic Sleep Patterns with Electrodermal Activity Akane Sano and Rosalind W. Picard, Massachusetts Institute of Technology Media

Objectives•Evaluate EDA sleep patterns

quantitatively from healthy groups

•Understand what the changing patterns of EDA mean in terms of traditional PSG.

ExperimentsCollected EDA+motion during sleep from healthy adults

Total: 168 nights

Page 6: Toward a Taxonomy of Autonomic Sleep Patterns with Electrodermal Activity Akane Sano and Rosalind W. Picard, Massachusetts Institute of Technology Media

0

Mot

ion

1 2 3 4 5 6 7 8

SWS

N-REM2

N-REM1

REM

W

Time [hr]

Analysis: sleep vs. wakeSleep and wake are discriminated from accelerometer data with standard zero-crossing and Cole’s function

wake

Page 7: Toward a Taxonomy of Autonomic Sleep Patterns with Electrodermal Activity Akane Sano and Rosalind W. Picard, Massachusetts Institute of Technology Media

Analysis: EDA storms during sleep• After low-pass filtering (0.4 Hz, 32nd order FIR filter), we detected

“storm” regions during sleep, regions of EDA with a burst of peaks

Storm epoch: > 3 peaks / 30-sec with the slope of each peak > 0.09 micro Siemens/s

Storm: Storm epochs that are adjacent or within 5 minutes of each other

Example: 6 storms in one night of sleep

*

* wake

EDA Storm

Raw EDA

Page 8: Toward a Taxonomy of Autonomic Sleep Patterns with Electrodermal Activity Akane Sano and Rosalind W. Picard, Massachusetts Institute of Technology Media

0

1

2

3

ED

A [m

icro

Sie

men

s]

0

Mot

ion

0

2

4

6

# of

S

torm

Pea

ks

1 2 3 4 5 6 7 8

SWSN-REM2N-REM1

REMW

Time [hr]

EDA vs. sleep stages from PSG

EDA raw data

Motion data

EDA peaks

Sleep Stage

Wake is red

Page 9: Toward a Taxonomy of Autonomic Sleep Patterns with Electrodermal Activity Akane Sano and Rosalind W. Picard, Massachusetts Institute of Technology Media

More than 90 % of EDA Storms occurred in SWS and NREM2 (N=7,

one night each) One subject had storms below the threshold

Portion of storm epochs in each category of sleep.

Page 10: Toward a Taxonomy of Autonomic Sleep Patterns with Electrodermal Activity Akane Sano and Rosalind W. Picard, Massachusetts Institute of Technology Media

0 3 6 9 12 15 180

10

20

30

40

50

60

# of Storms

Fre

qu

en

cy

Histogram of # of storms over night (168 nights)

2/3 of nights had >= 1 storm 1/2 of nights had >= 2

storms

Page 11: Toward a Taxonomy of Autonomic Sleep Patterns with Electrodermal Activity Akane Sano and Rosalind W. Picard, Massachusetts Institute of Technology Media

Summary• We analyzed electrodermal activity from healthy subjects

over 150 nights

• More than 90 % of EDA storms occurred in SWS and NREM2 (N=7, one night each)

• 2/3 of nights showed more than 1 EDA storm

1/2 of nights had more than 2 storms

Next Steps

• Needs more detail analysis with EEG and heart rates

• Are they related with sleep quality/ Sleep disorders

or Memory consolidation?