ETRI 라이프로그 데이터셋 (2020-2018)
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Description

******* 2020/2019-2018 데이터 업데이트: 2023. 2. 2  ******************************************

1. 실험자의 인구통계학적 정보가 수정되었습니다. (성별, 나이, 주사용 손, 키, 몸무게)


******* 2020/2019-2018 데이터 업데이트: 2022. 3. 17 ******************************************

1. 실험자의 인구통계학적 정보가 추가되었습니다. (성별, 나이, 주사용 손, 키, 몸무게)

2. 매일 오전 실험 시작 시 (AM), 그리고 실험 종료 시 (PM) 입력한 수면 관련 설문조사의 결과가 추가되었습니다.

3. Withings Sleep Mat (2020), Actigraph (2019), Fitbit Versa (2018)로 수집한 수면 측정 데이터가 추가되었습니다.

아래 본문의 설명을 참고하시기 바랍니다.

*******************************************************************************************************




일상생활 중 다양한 경험상황을 이해하기 위해 멀티모달 센서를 활용한 라이프로그 데이터셋을 구축하였습니다.

2020년 22명, 2019년 20명, 2018년 30명의 실험자로부터 총 1,285일의 실험일 동안 약 14,220시간의 데이터를 수집하였습니다.

데이터셋은 스마트폰의 IMU 및 GPS 데이터, E4의 가속도계, PPG, EDA, 서모파일 센서로부터 측정한 다양한 생리반응 신호,

그리고 사용자가 직접 입력한 행동, 환경, 및 감정 레이블을 포함합니다. 


* 데이터셋의 구성

==================================================================================================

+----- USER_ID

 |        +----- Unix_epoch_timestamp (DAY 1)

 |         |        +----- e4Acc

 |         |         |        timestamp (e4_accelerometer_data).csv 

 |         |         |        ...

 |         |        +----- e4Bvp

 |         |         |        timestamp (e4_blood_volume_pressure_data).csv 

 |         |         |        ...

 |         |        +----- e4Eda

 |         |         |        timestamp (e4_electrodermal_activity_data).csv 

 |         |         |        ...

 |         |        +----- e4Hr

 |         |         |        timestamp (e4_heart_rate_data).csv 

 |         |         |        ...

 |         |        +----- e4Temp

 |         |         |        timestamp (e4_skin_temperature_data).csv 

 |         |         |        ...

 |         |        +----- mAcc

 |         |         |        timestamp (mobile_accelerometer_data).csv 

 |         |         |        ...

 |         |        +----- mGps

 |         |         |        timestamp (mobile_gps_data).csv 

 |         |         |        ...

 |         |        +----- mGyr

 |         |         |        timestamp (mobile_gyroscope_data).csv 

 |         |         |        ...

 |         |        +----- mMag

 |         |         |        timestamp (mobile_magnetometer_data).csv 

 |         |         |        ...

 |         |        timestamp_label.csv

 |        +----- Unix_epoch_timestamp (DAY 2)

 |         |        +----- ...

==================================================================================================


* ETRI_Lifelog_Dataset_2020

2020 데이터셋은 다음의 데이터를 포함합니다.

==================================================================================================

- Triaxial acceleration force (in m/s^2) from the mobile phone accelerometer (30 Hz) and E4 accelerometer (32 Hz)

- Triaxial rate of rotation (in rad/s) and degrees of rotation (in Degrees) from the mobile phone gyroscope (30 Hz)

- Triaxial geomagnetic field strength (in μT) from the mobile phone magnetometer (30 Hz)

- Latitude and longitude, and horizontal accuracy* (in meters) from the mobile phone GPS (every 5 seconds)

- Blood volume pressure (in nano Watt) from E4 photoplethysmography (PPG) sensor (64 Hz)

- Electrodermal activity (skin conductance in μS) from E4 EDA sensor (4 Hz)

- Average** heart rate values (in bps) computed in 10 seconds-span based on the BVP analysis from E4 (1 Hz)

- Peripheral skin temperature (in Celsius degrees) from E4 infrared thermopile (4 Hz)


* The estimated horizontal accuracy is defined as the radius of 68% confidence according to the API.

Reference: https://developer.android.com/reference/android/location/Location#getAccuracy()

** HR values are not derived from a real-time reading but are created after the data collection session.

Reference: https://support.empatica.com/hc/en-us/articles/360029469772-E4-data-HR-csv-explanation


레이블 파일은 12개의 열로 구성되어 있으며, 다음의 정보를 포함합니다.

Column nameOptions (Descriptions)
ts
timestamp (Unix epoch time)
action

sleep, personal_care, work, study, household, care_housemem (caregiving), recreation_media, entertainment, outdoor_act (sports), hobby, recreation_etc (free time), shop, communitiy_interaction (regular activity), travel (includes commute), meal (includes snack), socialising

actionOption
Details of the selected action. See the description below.
actionSub

meal_amount when action=meal or snack

move_method when action=travel

actionSubOption

1 (light), 2 (moderate), 3 (heavy) when actionSub=meal_amount

1 (walk), 2 (driving), 3 (taxi, passenger), 4 (personal mobility), 5 (bus), 6 (train, subway), 7 (others) when actionSub=move_method

condition
ALONE, WITH_ONE, WITH_MANY
conditionSub1Option
1 (with families), 2 (with friends), 3 (with colleagues), 4 (acquaintances), 5 (others)
conditionSub2Option
1 (passive in conversation), 2 (moderate participation in conversation), 3 (active in conversation)
place
home, workplace, restaurant, outdoor, other_indoor
emotionPositive 
(negative) 1-2-3-4-5-6-7 (positive)
emotionTension
(relaxed) 1-2-3-4-5-6-7 (aroused)
activity***
0 (IN_VEHICLE), 1 (ON_BICYCLE), 2 (ON_FOOT), 3 (STILL), 4 (UNKNOWN), 5 (TILTING), 7 (WALKING), 8 (RUNNING)

*** Values in the activity column represent the detected activity of the mobile device using Google's Awareness API.

Reference: https://developers.google.com/android/reference/com/google/android/gms/location/DetectedActivity?hl=en


레이블 파일의 actionOption 열은 아래의 정보로 구성되어 있습니다.

==================================================================================================

111 Sleep

112 Sleepless

121 Meal

122 Snack

131 Medical services, treatments, sick rest

132 Personal hygiene (bath)

133 Appearance management (makeup, change of clothes)

134 Beauty-related services

211 Main job

212 Side job

213 Rest during work

22 Job search

311 School class / seminar (listening)

312 Break between classes

313 School homework, self-study (individual)

314 Team project (in groups)

321 Private tutoring (offline)

322 Online courses

41 Preparing food and washing dishes

42 Laundry and ironing

43 Housing management and cleaning

44 Vehicle management

45 Pet and plant caring

46 Purchasing goods and services (grocery/take-out)

51 Caring for children under 10 who live together

52 Caring for elementary, middle, and high school students over 10 who live together

53 Caring for a spouse

54 Caring for parents and grandparents who live together

55 Caring for other family members who live together

56 Caring for parents and grandparents who do not live together

57 Caring for other family members who do not live together

81 Personal care-related travel

82 Commuting and work-related travel

83 Education-related travel

84 Travel related to housing management

85 Travel related to caring for family and household members

86 Travel related to participation and volunteering

87 Socializing and leisure-related travel

61 Religious activities

62 Political activity

63 Ceremonial activities

64 Volunteer

711 Offline communication

712 Video or voice call

713 Text or email (Online)

721 Reading books, newspapers, and magazines

722 Watching TV or video

723 Listening to audio

724 Internet search or blogging

725 Gaming (mobile, computer, video)

741 Watching a sporting event

742 Watching movie

743 Concerts and plays

744 Art galleries and museums

744 Amusement Park, zoo

745 Festival, carnival

746 Driving, sightseeing, excursion

751 Walking

752 Running, jogging

753 Climbing, hiking

754 Biking

755 Ball games (soccer, basketball, baseball, tennis, etc)

756 Personal exercises (yoga, pilates, etc.)

756 Camping, fishing

761 Group games (board games, card games, puzzles, etc.)

762 Personal hobbies (woodworking, gardening, etc.)

763 Group performances (orchestra, choir, troupe, etc.)

764 Liberal arts and learning (languages, musical instruments, etc.)

791 Nightlife

792 Smoking

793 Do nothing and rest

91 Online shopping

92 Offline shopping

==================================================================================================


2020 데이터셋의 실험자별 데이터 통계는 다음과 같습니다.


******* 2020 데이터 업데이트: 2022. 3. 15 *******************************************************

1. 실험자의 인구통계학적 정보가 추가되었습니다. (성별, 나이, 주사용 손, 키, 몸무게)

2. 매일 오전 실험 시작 시 (AM), 그리고 실험 종료 시 (PM) 입력한 수면 관련 설문조사의 결과가 추가되었습니다.

ColumnDescriptions
amPm

am: Sleep related questionnaire was carried out in the morning.

pm: Questionnaire collected factors that may have affect on sleep, performed in the evening. 

sleep

Q. Are you satisfied with your sleep? (Subjective sleep quality score)

A. 1 (Not at all), 2 (Not much), 3 (Moderately)), 4 (Fairly), 5 (Fully)

sleepProblem

Q. Did you have problems during sleep?

A. 1 (It took more than 30 minutes to fall asleep.), 2 (I was awake during the night or prior to my scheduled wake time.), 3 (I was awake during the night to go to the bathroom.), 4 (I snored loudly during the sleep or woke up during the night choking.), 5 (I was disturbed by the low temperature during sleep.), 6 (I was disturbed by the high temperature during sleep.), 7 (I had nightmares.), 8 (I was disturbed by the pain.), 9 (I was disturbed by other reasons not listed above.), 0 (I did not have any problems.)

dream
1 (Nightmare), 2 (Neutral dream), 3 (Nice dream), 4 (None)
amCondition

Q. Do you feel refreshed after awakening? (Physical condition)

A. 1 (Not at all), 2 (Not much), 3 (Moderately), 4 (Fairly), 5 (Fully)

amEmotion

Q. How do you feel after awakening? (Emotional condition)

A. 1 (Very unpleasant), 2 (Unpleasant), 3 (Moderate), 4 (Pleasant), 5 (Very pleasant)

pmEmotion

Q. How do you feel now? (Emotional condition before you sleep)

A. 1 (Very unpleasant), 2 (Unpleasant), 3 (Moderate), 4 (Pleasant), 5 (Very pleasant)

pmStress

Q. How stressed are you today?

A. 1 (Very much), 2 (Fairly), 3 (As usual), 4 (Not much), 5 (Not at all)

pmFatigue

Q. How tired are you today? (Physical condition)

A. 1 (Very much), 2 (Fairly), 3 (As usual), 4 (Not much), 5 (Not at all)

caffeine
Types of beverages that contains caffeine, if any.
cAmount
Amount of caffeinated beverages (in ml).
alcohol
Types of beverages that contains alcohol, if any.
aAmountAmount of alcoholic beverages (in ml).

3. Withings Sleep Tracking Mat로 수집한 수면 측정 데이터가 추가되었습니다. (API)

실험 시 지급된 수면 측정 센서를 매트리스 아래에 설치하고 평소와 같이 수면을 취하도록 안내하였고,

수면 데이터는 Withings 모바일 앱을 통해 자동으로 서버로 전송되는 방식으로 수집하였습니다.

ColumnDescriptions
startDtStart date.
endDtEnd date.
lastUpdateTimestamp for requesting data that were updated or created after this date. Useful for data synchronization between systems.
wakeupduration
Time spent awake (in seconds).
lightsleepduration
Duration in state light sleep (in seconds).
deepsleepduration
Duration in state deep sleep (in seconds).
wakeupcount
Number of times the user woke up while in bed. Does not include the number of times the user got out of bed.
durationtosleep
Time to sleep (in seconds).
remsleepduration
Duration in state REM sleep (in seconds).
durationtowakeup
Time to wake up (in seconds).
hr_average
Average heart rate.
hr_min
Minimal heart rate.
hr_max
Maximal heart rate.
rr_average
Average respiration rate.
rr_min
Minimal respiration rate.
rr_max
Maximal respiration rate.
breathing_disturbances_intensity
Wellness metric, available for all Sleep and Sleep Analyzer devices. Intensity of breathing disturbances
snoring
Total snoring time
snoringepisodecount
Numbers of snoring episodes of at least one minute
sleep_score
Sleep score

*******************************************************************************************************

*******************************************************************************************************


* ETRI_Lifelog_Dataset_2019_2018

2019, 2018 데이터셋은 다음의 데이터를 포함합니다.

==================================================================================================

- Triaxial acceleration force (in m/s^2) from the mobile phone accelerometer (30 Hz) and E4 accelerometer (32 Hz)

- Triaxial rate of rotation (in rad/s) and degrees of rotation (in Degrees) from the mobile phone gyroscope (30 Hz)

- Triaxial geomagnetic field strength (in μT) from the mobile phone magnetometer (30 Hz)

- Latitude and longitude, and horizontal accuracy* (in meters) from the mobile phone GPS (every 1 minute)

- Blood volume pressure (in nano Watt) from E4 photoplethysmography (PPG) sensor (64 Hz)

- Electrodermal activity (skin conductance in μS) from E4 EDA sensor (4 Hz)

- Average** heart rate values (in bps) computed in 10 seconds-span based on the BVP analysis from E4 (1 Hz)

- Peripheral skin temperature (in Celsius degrees) from E4 infrared thermopile (4 Hz)


* The estimated horizontal accuracy is defined as the radius of 68% confidence according to the API.

Reference: https://developer.android.com/reference/android/location/Location#getAccuracy()

** HR values are not derived from a real-time reading but are created after the data collection session.

Reference: https://support.empatica.com/hc/en-us/articles/360029469772-E4-data-HR-csv-explanation


레이블 파일은 12개의 열로 구성되어 있으며, 다음의 정보를 포함합니다.

Column nameOptions (Descriptions)
ts
timestamp (Unix epoch time)
action

sleep, personal_care, work, study, household, recreation_media, entertainment, outdoor_act (sports), hobby, recreation_etc (free time), communitiy_interaction (regular activity), travel (includes commute), meal (includes snack), socialising

actionOption
0 (walking upstairs), 1 (walking downstairs), 2 (walking), 3 (sitting), 4 (lying), 5 (standing), 6 (running)
actionSub0 (on the table), 1 (in the pocket), 2 (in hand), 3 (others), 4 (in the bag)
actionSubOption
0 (on bicycle), 1 (on foot), 2 (driving), 3 (public transportation), 4 (personal mobility)
condition
0 (alone), 1 (family member), 2 (friend), 3 (collegue), 4 (acquaintance)
conditionSub1Option
1 (family member), 2 (friend), 3 (collegue), 4 (acquaintance)
conditionSub2Option
1 (online)
place
home, workplace, restaurant, outdoor, other_indoor
emotionPositive 
(negative) 1-2-3-4-5-6-7 (positive)
emotionTension
(relaxed) 1-2-3-4-5-6-7 (aroused)
activity***
0 (IN_VEHICLE), 1 (ON_BICYCLE), 2 (ON_FOOT), 3 (STILL), 4 (UNKNOWN), 5 (TILTING), 7 (WALKING), 8 (RUNNING)

*** Values in the activity column represent the detected activity of the mobile device using Google's Awareness API.

Reference: https://developers.google.com/android/reference/com/google/android/gms/location/DetectedActivity?hl=en


2019, 2018 데이터셋의 실험자별 데이터 통계는 다음과 같습니다.



******* 2019-2018 데이터 업데이트: 2022. 3. 17 ************************************************

1. 실험자의 인구통계학적 정보가 추가되었습니다. (성별, 나이, 키, 몸무게)

2. 매일 오전 실험 시작 시 (AM), 그리고 실험 종료 시 (PM) 입력한 수면 관련 설문조사의 결과가 추가되었습니다.

ColumnDescriptions
amPm

am: Sleep related questionnaire was carried out in the morning.

pm: Questionnaire collected factors that may have affect on sleep, performed in the evening. 

sleep

Q. Are you satisfied with your sleep? (Subjective sleep quality score)

A. 1 (Not at all), 2 (Not much), 3 (Moderately)), 4 (Fairly), 5 (Fully)

sleepProblem

Q. Did you have problems during sleep?

A. 1 (It took more than 30 minutes to fall asleep.), 2 (I was awake during the night or prior to my scheduled wake time.), 3 (I was awake during the night to go to the bathroom.), 4 (I snored loudly during the sleep or woke up during the night choking.), 5 (I was disturbed by the low temperature during sleep.), 6 (I was disturbed by the high temperature during sleep.), 7 (I had nightmares.), 8 (I was disturbed by the pain.), 9 (I was disturbed by other reasons not listed above.), 0 (I did not have any problems.)

dream
1 (Nightmare), 2 (Neutral dream), 3 (Nice dream), 4 (None)
amCondition

Q. Do you feel refreshed after awakening? (Physical condition)

A. 1 (Not at all), 2 (Not much), 3 (Moderately), 4 (Fairly), 5 (Fully)

amEmotion

Q. How do you feel after awakening? (Emotional condition)

A. 1 (Very unpleasant), 2 (Unpleasant), 3 (Moderate), 4 (Pleasant), 5 (Very pleasant)

pmEmotion

Q. How do you feel now? (Emotional condition before you sleep)

A. 1 (Very unpleasant), 2 (Unpleasant), 3 (Moderate), 4 (Pleasant), 5 (Very pleasant)

pmStress

Q. How stressed are you today?

A. 1 (Very much), 2 (Fairly), 3 (As usual), 4 (Not much), 5 (Not at all)

ifUnusual

Q. Was it an unusual day? 

A. 1 (Yes), 2 (No)

breakfast

Q. Were you satisfied with today's breakfast?

A. 1 (Not at all), 2 (Moderately), 3 (Fully), 4 (Not applicable)

lunch

Q. Were you satisfied with today's lunch?

A. 1 (Not at all), 2 (Moderately), 3 (Fully), 4 (Not applicable)

dinner

Q. Were you satisfied with today's dinner?

A. 1 (Not at all), 2 (Moderately), 3 (Fully), 4 (Not applicable)

lateSnack

Q. Were you satisfied with today's midnight snack?

A. 1 (Not at all), 2 (Moderately), 3 (Fully), 4 (Not applicable)

amCaffeine
Types of caffeinated beverages consumed in the morning.
amCaffAmount
Amount of caffeinated beverages consumed in the morning (in cups).
pmCaffeine
Types of caffeinated beverages consumed in the afternoon.
pmCaffAmount
Amount of caffeinated beverages consumed in the afternoon (in cups).
alcohol
Types of beverages that contains alcohol, if any.
aAmountAmount of alcoholic beverages (in bottles).

3. ActiGraph (2019 dataset), Fitbit Versa (2018 dataset)로 수집한 수면 측정 데이터가 추가되었습니다.

ColumnDescriptions
startDtStart date.
endDtEnd date.
deviceDevice used to measure the sleep related data during the night sleep. Actigraph (2019), Fitbit Versa (2018)
sleep_score
Sleep score.
total_sleep_time
Duration of sleep (in seconds).
time_in_bed
Duration of time in bed (in seconds).
waso
Wake After Sleep Onset (WASO)
wakeupcount
Number of times the user woke up while in bed. Does not include the number of times the user got out of bed.
aal
Average Awakening Length (AAL)
movement_index
Movement Index (MI), The total of scored awake minutes divided by Total time in bed in hours x 100.
fragmentation_index
Fragmentation Index (FI),The percentage of one minute periods of sleep vs. all periods of sleep in the sleep period.
sleep_fragmentation_index
The sum of MI and FI.

*******************************************************************************************************

*******************************************************************************************************


* 본 데이터셋을 활용할 경우 다음 논문을 인용 바랍니다.

Seungeun Chung, Chi Yoon Jeong, Jeong Mook Lim, Jiyoun Lim, Kyoung Ju Noh, Gague Kim, Hyuntae Jeong,

Real-world multimodal lifelog dataset for human behavior study. ETRI Journal 43(6), 2021 

https://doi.org/10.4218/etrij.2020-0446


* 관련 논문

Jiyoun lim, Chi Yoon Jeong, Jeong Muk Lim, Seungeun Chung, Gague Kim, Kyoung Ju Noh, Hyuntae Jeong

Assessing Sleep Quality Using Mobile EMAs: Opportunities, Practical Consideration, and Challenges. IEEE Access 10, 2022

https://doi.org/10.1109/ACCESS.2021.3140074


Seungeun Chung, Jiyoun Lim, Kyoung Ju Noh, Gague Kim, Hyuntae Jeong, 

Sensor Data Acquisition and Multimodal Sensor Fusion for Human Activity Recognition Using Deep Learning. Sensors 19(7), 2019

https://doi.org/10.3390/s19071716


Jiyoun Lim, Seunghee Yoo, Seungeun Chung, Gague Kim, Kyoung Ju Noh, Jeong Muk Lim, Hyuntae Jeong:

SPER: Stay-Point Extraction considering Revisits in a Single Trajectory. ICTC 2021

https://doi.org/10.1109/ICTC52510.2021.9621139


임호연, 정승은, 정치윤, 정현태,

라이프로그 기반 일상생활 활동유형에 대한 탐색적 연구, 한국정보처리학회 추계 학술대회, 2020

https://library.etri.re.kr/service/rsch/etri-article/down.htm?view=open&resultId=0000062797


Jiyoun Lim, Seungeun Chung, Kyoung Ju Noh, Gague Kim, Hyun-Tae Jeong,

An empirical study on finding experience sampling parameters to explain sleep quality based on dimension reduction. ICTC 2019

https://doi.org/10.1109/ICTC46691.2019.8939976


Seungeun Chung, Inyoung Hwang, Jiyoun Lim, Hyun-Tae Jeong,

Finding Points-of-Interest (PoIs) from Life-logging and Location Trace Data. ICTC 2019

https://doi.org/10.1109/ICTC46691.2019.8940021


Seungeun Chung, Jiyoun Lim, Kyoung Ju Noh, Gague Kim, Hyun-Tae Jeong,

Sensor Positioning and Data Acquisition for Activity Recognition using Deep Learning. ICTC 2018

https://doi.org/10.1109/ICTC.2018.8539473


데이터 파일 (총 15 개)
2018 data

요약 ETRI_Lifelog_Dataset...

  • 등록일  2021-12-15
  • 파일명   datas...
  • 크기  11.3GB
  • 다운로드 수  376
2018 data

요약 ETRI_Lifelog_Dataset...

  • 등록자  정승은
  • 파일명   dataset_2018.7z
  • 크기  11.3GB
  • 다운로드 수  376
ETRI_Lifelog_Dataset_2019_2018
2019 data

요약 ETRI_Lifelog_Dataset...

  • 등록일  2021-12-15
  • 파일명   datas...
  • 크기  10.0GB
  • 다운로드 수  295
2019 data

요약 ETRI_Lifelog_Dataset...

  • 등록자  정승은
  • 파일명   dataset_2019.7z
  • 크기  10.0GB
  • 다운로드 수  295
ETRI_Lifelog_Dataset_2019_2018
2019-2018 수면 측정 데이터

요약 2019-2018 데이터 업데이트 (...

  • 등록일  2022-03-17
  • 파일명   user_...
  • 크기  59.6KB
  • 다운로드 수  192
2019-2018 수면 측정 데이터

요약 2019-2018 데이터 업데이트 (...

  • 등록자  정승은
  • 파일명   user_sleep_2019...
  • 크기  59.6KB
  • 다운로드 수  192

2019-2018 데이터 업데이트 (2022.3.17)

2019-2018 수면관련 설문결과

요약 2019-2018 데이터 업데이트 (...

  • 등록일  2022-03-17
  • 파일명   user_...
  • 크기  62.7KB
  • 다운로드 수  177
2019-2018 수면관련 설문결과

요약 2019-2018 데이터 업데이트 (...

  • 등록자  정승은
  • 파일명   user_survey_201...
  • 크기  62.7KB
  • 다운로드 수  177

2019-2018 데이터 업데이트 (2022.3.17)

2019-2018 실험자별 정보

요약 2019-2018 데이터 업데이트 (...

  • 등록일  2022-03-17
  • 파일명   user_...
  • 크기  1.9KB
  • 다운로드 수  156
2019-2018 실험자별 정보

요약 2019-2018 데이터 업데이트 (...

  • 등록자  정승은
  • 파일명   user_info_2019_...
  • 크기  1.9KB
  • 다운로드 수  156

2019-2018 데이터 업데이트 (2022.3.17)

2019-2018 수정 업데이트 (2023.2.2)

2020 수면 측정 데이터

요약 2020 데이터 업데이트 (2022....

  • 등록일  2022-03-15
  • 파일명   user_...
  • 크기  73.3KB
  • 다운로드 수  260
2020 수면 측정 데이터

요약 2020 데이터 업데이트 (2022....

  • 등록자  정승은
  • 파일명   user_sleep_2020...
  • 크기  73.3KB
  • 다운로드 수  260
2020 데이터 업데이트 (2022.3.15)
2020 수면관련 설문결과

요약 2020 데이터 업데이트 (2022....

  • 등록일  2022-03-15
  • 파일명   user_...
  • 크기  89.4KB
  • 다운로드 수  245
2020 수면관련 설문결과

요약 2020 데이터 업데이트 (2022....

  • 등록자  정승은
  • 파일명   user_survey_202...
  • 크기  89.4KB
  • 다운로드 수  245
2020 데이터 업데이트 (2022.3.15)

2020 실험자별 정보

요약 2020 데이터 업데이트 (2022....

  • 등록일  2022-03-15
  • 파일명   user_...
  • 크기  1.1KB
  • 다운로드 수  244
2020 실험자별 정보

요약 2020 데이터 업데이트 (2022....

  • 등록자  정승은
  • 파일명   user_info_2020....
  • 크기  1.1KB
  • 다운로드 수  244

2020 데이터 업데이트 (2022.3.15)

README 2019-2018

요약 ETRI_Lifelog_Dataset...

  • 등록일  2021-12-15
  • 파일명   READM...
  • 크기  6.9KB
  • 다운로드 수  228
README 2019-2018

요약 ETRI_Lifelog_Dataset...

  • 등록자  정승은
  • 파일명   README_2019.txt
  • 크기  6.9KB
  • 다운로드 수  228
ETRI_Lifelog_Dataset_2019_2018
README 2020

요약 ETRI_Lifelog_Dataset...

  • 등록일  2021-12-15
  • 파일명   READM...
  • 크기  9.5KB
  • 다운로드 수  244
README 2020

요약 ETRI_Lifelog_Dataset...

  • 등록자  정승은
  • 파일명   README_2020.txt
  • 크기  9.5KB
  • 다운로드 수  244
ETRI_Lifelog_Dataset_2020
user01-06 data

요약 ETRI_Lifelog_Dataset...

  • 등록일  2021-12-15
  • 파일명   user0...
  • 크기  5.6GB
  • 다운로드 수  346
user01-06 data

요약 ETRI_Lifelog_Dataset...

  • 등록자  정승은
  • 파일명   user01-06.7z
  • 크기  5.6GB
  • 다운로드 수  346
ETRI_Lifelog_Dataset_2020
user07-10 data

요약 ETRI_Lifelog_Dataset...

  • 등록일  2021-12-15
  • 파일명   user0...
  • 크기  5.9GB
  • 다운로드 수  268
user07-10 data

요약 ETRI_Lifelog_Dataset...

  • 등록자  정승은
  • 파일명   user07-10.7z
  • 크기  5.9GB
  • 다운로드 수  268
ETRI_Lifelog_Dataset_2020
user11-12 data

요약 ETRI_Lifelog_Dataset...

  • 등록일  2021-12-15
  • 파일명   user1...
  • 크기  3.5GB
  • 다운로드 수  299
user11-12 data

요약 ETRI_Lifelog_Dataset...

  • 등록자  정승은
  • 파일명   user11-12.7z
  • 크기  3.5GB
  • 다운로드 수  299
ETRI_Lifelog_Dataset_2020
user21-25 data

요약 ETRI_Lifelog_Dataset...

  • 등록일  2021-12-15
  • 파일명   user2...
  • 크기  5.1GB
  • 다운로드 수  242
user21-25 data

요약 ETRI_Lifelog_Dataset...

  • 등록자  정승은
  • 파일명   user21-25.7z
  • 크기  5.1GB
  • 다운로드 수  242
ETRI_Lifelog_Dataset_2020
user26-30 data

요약 ETRI_Lifelog_Dataset...

  • 등록일  2021-12-15
  • 파일명   user2...
  • 크기  5.1GB
  • 다운로드 수  256
user26-30 data

요약 ETRI_Lifelog_Dataset...

  • 등록자  정승은
  • 파일명   user26-30.7z
  • 크기  5.1GB
  • 다운로드 수  256
ETRI_Lifelog_Dataset_2020