This files provides information on the ATOM-HP dataset comprising summaries and per-subject data files in CSV format.
The complete dataset is available at https://br-atomhp.usc.edu (includes data from PDMS website - VPN required)
The data collected through the PDMS website is available at https://pdms.usc.edu/export. These are options to get a local copy.
With Filezilla, sftp to pdms.usc.edu as atom-hp then navigate to /var/www/html/export.
mkdir data; cd -
scp -r atom-hp@pdms.usc.edu:/var/www/html/export/* .mkdir data; cd -
wget -r --no-parent -nH --cut-dirs=1 --reject "index.html*" --user=atom-hp --password=<PASSWORD> https://pdms.usc.edu/export/Kinect1 Band1 Chemo1 Kinect2 Chemo2 Band2 Followup150
|--------|------------|-------|----------|-------------|----------------------|Subject ids for clinical study are 001-060 and 120-150.
CRF are stored in RedCap.
Visit1: date of visit 1 corresponding to Kinect1 recordings (date of “Visit 1 CRF”)
Visit2: date of visit 2 corresponding to Kinect2 recordings (date of “Visit 2 CRF”)
Kinect1: Kinect file recording date and time of first recording
Kinect2: Kinect files recording date and time of second recording
Band1: day band data collection starts (date of “screening CRF”)
Band2: day band data collection must stop (on day 60 of study)
Chemo1: date of first chemo
Chemo2: date of second chemo
Followup150: day of follow-up (on day 150 of study)
Band data records made during [Chemo1, Chemo2].
Kinect recordings made during [Visit1, Visit2]. Note that Visit1, Visit2 may differ from Chemo1, Chemo2.
Day 1 Day 2 Day 3 Day 4 Day 5
Exercise
|------------|------------|--o-o-------|------------|------------|
Kinect1 Kinect2Subject ids for military study are 061-120. Band data collection made over 5 days, Kinect recordings in day 3, 6-9AM before and after exercise.
mil_cases_151216.csv contains military cases measurements corresponding to the data in MilitaryRawData_15DEC16.xlsx. Measuremnts contain demographics and CFT assessment scores.
id
age: in years
service_time_mos: service time military occupational specialty
mos:subjects military occupational specialty (i.e. mortarman, rifleman, radio operator, etc...)
rank:
prior_cft_score: [0, 300]
marksman: 1=expert > 2=sharp shooter > 3=marksman, 4=NA or not reported
deployments:
ethnicity: 1= asian, 2= black non-hispanic, 3= caucasian non-hispanic, 4= hispanic, 5= native american/eskimo, 6= pacific islander/hawaiian, 7= other
height: (in)
weight: (lbs)
cigarette_use: 1= never smoked, 2= experimented with smoking, 3= occasional smoker, 4= daily smoker, 5= former smoker
chewing_tobacco_use: 1= never used smokeless tobacco, 2= experimented with smokeless tobacco, 3= occasional user, 4= daily user, 5= former user
pre_test_a: (s)
pre_test_b: (s)
post_test_a: (s)
post_test_b: (s)
pre_marksmanship_score: [0, 50]
pre_marksmanship_group_size: (cm)
pre_marksmanship_mpiczp: Mean point of impact from the center of the target. Theoretically shots are aimed at the center of the target so it demonstrates how far off the group size is from the center of the target. (cm)
post_marksmanship_score: [0, 50]
post_marksmanship_group_size: (cm)
post_marksmanship_mpiczp: (cm)
cft_run_time: (s)
cft_manuf_time: maneuver under fire time (s)
cft_lift_count: number of hammo can lift performed
cft_runs_score: [0, 100]
cft_manufs_score: maneuver under fire score [0, 100]
cft_lift_score: of hammo can lift score [0, 100]
cft_score: total CFT score (cft_lift_score + cft_runs_score + cft_manufs_score) [0, 300]Per subject files are named as follows:
P###_DATA_TYPE_#_TASK_#_REP_#_[XRF_FILENAME].csvP###: subject id, military indices are 061-120, the other are all clinical.
DATA_TYPE:
BAND: MS Band data.
KINECT_METADATA: Kinect metadata.
KINECT_SKELETON: Kinect skeleton data.
KINECT_FACE_PARAMS: Kinect face sensing parameters (military only).
KINECT_FACE_MESH: Kinect face mesh vertices (military only).
MIL_METRICS: Military (military only).
PRO: patient reported outcomes (PRO) data (clinical only).
REDCAP: clinical data (clinical only).
VISIT_#: 1 for Visit1, 2 for Visit2
TASK_#: 1 for ChairToTable, 2 for GetUpAndWalk, 3 for WalkAndTalk
REP_#: repeated measurements ordered by time (starts at 1)
email: account email
start_time: start time of the summary
end_time: end time of the summary
period: period of the summary (1: daily, 2: hourly)
steps: The total of steps taken in the time period
active_hours: Number of active hours in the period, used for Daily summary
total_calories: Total calories burned in the period
average_heart_rate: Average heart rate during the period
peek_heart_rate: Peak heart rate during the period
lowest_heart_rate: Lowest heart rate during the period
total_distance: Total distance in the period
total_distance_on_foot: Total distance covered on foot
actual_distance: Absolute distance, including any paused time
elevation_gain: Cumulative elevation gain during the period
elevation_loss: Cumulative elevation loss during the period
max_elevation: Maximum elevation during the period
min_elevation: Minimum elevation during the period
way_point_distance: Distance in cm used to waypoint the GPS data
speed: Total Period distance divided by period duration
pace: Period duration divided by total period distance
overall_pace: Duration of all periods divided by distance of all periodsvisit_number: visit number (eg. visit 1, visit 2.)
filename: Kinect recording raw file name
file_length: Kinect recording raw file size (in Byte)
creation_time: created/accessed time in recording file properties
email: account email
comment: comments from the coordinator
success: KinectVerifier recording validation code: 1 is Pass, 2 is Fail
task: 1 is ChairToTable (clinical), 2 is GetUpAndWalk (clinical), 3 is WalkAndTalk (military)See https://msdn.microsoft.com/en-us/library/dn799273.aspx
unix_timestamp: Unix timestamp of recording replaying/data extraction time
frame_number: frame index
spine_base_x, spine_base_y, spine_base_z, spine_mid_x, spine_mid_y, spine_mid_z, neck_x, neck_y, neck_z, head_x, head_y, head_z, shoulder_left_x, shoulder_left_y, shoulder_left_z, elbow_left_x, elbow_left_y, elbow_left_z, wrist_left_x, wrist_left_y, wrist_left_z, hand_left_x, hand_left_y, hand_left_z, shoulder_right_x, shoulder_right_y, shoulder_right_z, elbow_right_x, elbow_right_y, elbow_right_z, wrist_right_x, wrist_right_y, wrist_right_z, hand_right_x, hand_right_y, hand_right_z, hip_left_x, hip_left_y, hip_left_z, knee_left_x, knee_left_y, knee_left_z, ankle_left_x, ankle_left_y, ankle_left_z, foot_left_x, foot_left_y, foot_left_z, hip_right_x, hip_right_y, hip_right_z, knee_right_x, knee_right_y, knee_right_z, ankle_right_x, ankle_right_y, ankle_right_z, foot_right_x, foot_right_y, foot_right_z, spine_shoulder_x, spine_shoulder_y, spine_shoulder_z, hand_tip_left_x, hand_tip_left_y, hand_tip_left_z, thumb_left_x, thumb_left_y, thumb_left_z, hand_tip_right_x, hand_tip_right_y, hand_tip_right_z, thumb_right_x, thumb_right_y, thumb_right_z: skeleton joints coordinatesSee https://msdn.microsoft.com/en-us/library/dn782034.aspx
unix_timestamp: from replay
frame_number: first frame corresponds to the first frame in which the face is detected in the recording
happy: The user appears to be smiling and is putting forward a happy expression. This will also pick up smiles during laughter. It’s important to note that some users appear happy even when they are not, so this should not be considered an exact translation to emotion.
engaged: Combines results from LookingAway and Eye Closed to determine if user is engaged with content.
wearing_glasses: The user is wearing glasses.
left_eye_closed: The user's left eye is closed.
right_eye_closed: The user's right eye is closed.
mouth_open: The user's mouth is open.
mouth_moved: The user's mouth moved. This is the only property that needs frame over frame results to make an accurate determination. This feature works best if the user's head is mostly still.
looking_away: Determines if the user is looking away from the content. The detection is not refined enough to detect slight eye gaze shifts but it will detect larger head movements like looking over to talk to someone or looking down to check your phone.Detection Result Description:
Yes: We are very certain that the property is true and you could take a destructive action on this result.
No: We are very certain that the property is false and you could take a destructive action on this result.
Maybe: We are pretty sure that the property is true. You could reward the user or give a positive action for this result. For most properties, you could potentially infer from this result that the corresponding movement was small.
Unknown: We don’t have enough information to make a determination. This typically occurs because the user has orientated their face away from the sensor and we don’t want to give a bad result.Patient reported outcomes (PRO) data. The PRO scales are using come from the NIH PROMIS measures: http://www.healthmeasures.net/explore-measurement-systems/promis. See details in ATOM_HP_PRO.doc on how to use the PRO scale. We adapted the fatigue short form for use in daily measurement.
References: Junghaenel, Doerte U., et al. “Identification of distinct fatigue trajectories in patients with breast cancer undergoing adjuvant chemotherapy.” Supportive Care in Cancer 23.9 (2015): 2579-2587.
Christodoulou, Christopher, et al. “Measuring daily fatigue using a brief scale adapted from the Patient-Reported Outcomes Measurement Information System (PROMIS®).” Quality of Life Research 23.4 (2014): 1245-1253.
study_id
day
Chemo
FATEXP16,FATEXP18,FATEXP18_w,FATEXP20,FATEXP20_w,FATEXP5,FATEXP5_w,FATEXP6,FATIMP21_w,FATIMP3,FATIMP30,FATIMP30_w,FATIMP33,FATIMP33_w,FATIMP40_w,IsoCaPS1,IsoCaPS2,PFA01,PFA03,PFA05,PFA11,PFA16,PFA55,PFB26,PFC36,PFC37,PFC45,SDS001,Sleep108,Sleep109,Sleep110,Sleep115,Sleep116,Sleep44,Sleep87,Sleep90,UCLA11x2,UCLA13x3,UCLA14x2,UCLA18x2: PRO
WeightDoes not make sense to exported alphabetically!
study_id,
adv_events_v2
age
ante_weight_loss_10per_v1
ante_weight_loss_5per_v1
antiemetic_plan_v1
antiemetic_plan_v2
baseline_adv_events_v1
blood_press_v1
blood_press_v2
bmi_v1
bmi_v2
cancer_diagnosis
changes_chemo_plan_v2
chemo_day1_date_v2_1
chemo_day1_date_v2_2
chemo_day1_date_v2_3
chemo_day1_date_v2_4
chemo_intent
chemo_plan
clinical_site
concom_meds_v1
concom_meds_v2
coord_ecog_v1
coord_ecog_v2
coord_ecog_v3
coord_karnofsky_v1
coord_karnofsky_v2
datacol_start_date
datacol_stop_date
date_cancer_diag
day_followup_crf_complete
dayhosp_visits_day1_30_v3
dayhosp_visits_day31_60_v3
dayhosp_visits_day61_150_v3
dhospvis_day1_30_n_v3
dhospvis_day31_60_n_v3
dhospvis_day61_150_n_v3
dis_stat_2rounds_v3
dis_stat_study_start_v3
draw_comments
draw_date
draw_time
education
ethnicity
flow_rate_v1
flow_rate_v2
gender
grad_degree
heart_rate_v1
heart_rate_v2
height_units_v1
height_units_v2
height_v1
height_v2
hosp_day1_30_n_v3
hosp_day31_60_n_v3
hosp_day61_150_n_v3
hospital_day1_30_v3
hospital_day31_60_v3
hospital_day61_150_v3
inspired_o2_v1
inspired_o2_v2
marital_status
occupation
oxygen_sat_v1
oxygen_sat_v2
patient_ecog_v1
patient_ecog_v2
patient_ecog_v3
patient_karnofsky_v1
patient_karnofsky_v2
phys_ecog_v1
phys_ecog_v2
phys_ecog_v3
phys_karnofsky_v1
phys_karnofsky_v2
phys_visits_day1_30_v3
phys_visits_day31_60_v3
phys_visits_day61_150_v3
physvis_day1_30_n_v3
physvis_day31_60_n_v3
physvis_day61_150_n_v3
present_stage
presently_employed
rad_therapy_notes_v2
rad_therapy_v2
resp_rate_v1
resp_rate_v2
screening_crf_complete
screening_date
stage_at_diag
visit1_date
visit2_date
visit_1_crf_complete
visit_2_crf_complete
weight_units_v1
weight_units_v2
weight_v1
weight_v2