Digital Health Wearable Activity Logs
This dataset provides detailed daily logs of simulated wearable device users, including physical activity metrics, sleep stages, heart rate, biometrics, and mood. It enables robust analysis of wellness trends, behavioral patterns, and health outcomes, making it ideal for research, product development, and personalized health analytics.
Sample rows
preview · 8 of 200 rows · all 21 columns| user_idstring | sleep_efficiencyfloat | log_datedate | device_idstring | stepsinteger | distance_kmfloat | active_minutesinteger | calories_burnedfloat | resting_heart_rateinteger | max_heart_rateinteger | avg_heart_rateinteger | sleep_duration_minutesinteger | deep_sleep_minutesinteger | light_sleep_minutesinteger | rem_sleep_minutesinteger | awake_minutesinteger | body_temperature_cfloat | blood_oxygen_percentfloat | stress_levelinteger | mood_scoreinteger | notesstring |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| U001 | 92.4 | 2024-04-01 | D-Z123 | 13221 | 10.9 | 102 | 889.2 | 62 | 168 | 105 | 415 | 97 | 202 | 68 | 48 | 36.7 | 98.4 | 17 | 8 | blank |
| U002 | 90.2 | 2024-04-01 | D-M456 | 4890 | 4.1 | 41 | 362.7 | 72 | 139 | 94 | 392 | 56 | 185 | 55 | 41 | 36.6 | 97.1 | 36 | 6 | blank |
| U003 | 90.9 | 2024-04-01 | D-A789 | 17322 | 13.3 | 121 | 1152.4 | 59 | 181 | 113 | 382 | 104 | 197 | 71 | 10 | 36.5 | 99.2 | 14 | 10 | Ran 10k event |
| U004 | 0 | 2024-04-01 | D-B321 | 0 | 0 | 0 | 0 | 112 | 148 | 91 | 0 | 0 | 0 | 0 | 0 | 38.7 | 83.1 | 98 | 1 | Ill at home, fever |
| U005 | 85.2 | 2024-04-01 | D-C654 | 3521 | 2.7 | 33 | 282.8 | 76 | 129 | 87 | 375 | 45 | 154 | 41 | 40 | 36.8 | 96.5 | 28 | 7 | blank |
| U006 | 93.1 | 2024-04-01 | D-F420 | 12011 | 9.7 | 110 | 921.3 | 67 | 173 | 108 | 401 | 90 | 180 | 74 | 36 | 36.4 | 99 | 19 | 9 | blank |
| U007 | 68.1 | 2024-04-01 | D-G101 | 24502 | 20.4 | 183 | 1599.7 | 52 | 208 | 132 | 244 | 41 | 112 | 26 | 65 | 36 | 97.3 | 43 | 7 | Participated in marathon |
| U008 | 94.4 | 2024-04-01 | D-T999 | 6011 | 5.4 | 51 | 457.5 | 74 | 136 | 97 | 489 | 81 | 206 | 61 | 38 | 36.3 | 97.5 | 23 | 8 | blank |
| U009 | blank | 2024-04-01 | blank | blank | blank | blank | blank | 68 | 128 | 86 | blank | blank | blank | blank | blank | 36.2 | 98.1 | 22 | 8 | Device not worn |
| U010 | 88.7 | 2024-04-01 | D-X888 | 9512 | 7 | 78 | 612.6 | 66 | 145 | 99 | 410 | 60 | 192 | 50 | 35 | 36.7 | 96.9 | 18 | 9 | blank |
| U011 | 82.6 | 2024-04-01 | D-K111 | 4470 | 3.8 | 38 | 323.1 | 74 | 129 | 93 | 398 | 47 | 174 | 51 | 38 | 36.5 | 97.7 | 31 | 7 | blank |
| U012 | 94.2 | 2024-04-01 | D-Q222 | 17118 | 13.9 | 127 | 1101.9 | 61 | 175 | 116 | 491 | 104 | 219 | 84 | 32 | 36.1 | 99.4 | 8 | 10 | Long hike |
| U013 | 85.4 | 2024-04-01 | D-V333 | 15208 | 11.2 | 97 | 854.3 | 57 | 163 | 109 | 369 | 86 | 140 | 65 | 38 | 36.2 | 98.7 | 15 | 9 | blank |
| U014 | 0 | 2024-04-01 | D-P444 | 701 | 0.8 | 6 | 123.6 | 91 | 119 | 74 | 0 | 0 | 0 | 0 | 0 | 34.6 | 74.1 | 99 | 2 | ER visit overnight |
| U015 | 88.6 | 2024-04-01 | D-J555 | 8739 | 6.2 | 67 | 578.2 | 72 | 142 | 98 | 422 | 52 | 170 | 54 | 39 | 36.7 | 97 | 24 | 8 | blank |
| U016 | 0 | 2024-04-01 | D-H666 | 0 | 0 | 0 | 0 | 108 | 210 | 130 | 0 | 0 | 0 | 0 | 0 | 38.1 | 76.9 | 100 | 1 | Flu symptoms, stayed in bed |
| U017 | 67.7 | 2024-04-01 | D-T777 | 18445 | 14.6 | 145 | 1322.1 | 54 | 202 | 124 | 312 | 40 | 110 | 45 | 117 | 36.4 | 99.1 | 49 | 5 | Intense training |
| U018 | 93 | 2024-04-02 | D-S888 | 5802 | 4.9 | 54 | 388.7 | 69 | 133 | 91 | 439 | 90 | 197 | 62 | 41 | 36.8 | 98.2 | 19 | 7 | blank |
| U019 | 86.1 | 2024-04-02 | D-N999 | 15172 | 11.3 | 104 | 888 | 60 | 161 | 112 | 398 | 84 | 181 | 52 | 40 | 36.2 | 98.8 | 15 | 9 | blank |
| U020 | 91.6 | 2024-04-02 | D-R777 | 10225 | 7.9 | 89 | 702.5 | 64 | 154 | 101 | 488 | 102 | 216 | 62 | 34 | 36.5 | 97.9 | 23 | 8 | blank |
What the 200 rows show
from the 200-row sample- 86.8median sleep_
efficiency - 9,045median steps
- 7.0median distance_
km - 67.5median active_
minutes - 595.7median calories_
burned - 67median resting_
heart_ rate
Median 86.8, from 0.0 to 96.7.
- string 3
- integer 12
- float 5
- date 1
Columns
21 columns in three groups| column | type | description | example |
|---|---|---|---|
| Text 3 columns | |||
user_id | string | Unique identifier for each simulated wearable user | U001 |
device_id | string | Unique identifier for the wearable device used to collect the dataoptional | D-Z123 |
notes | string | Optional user or system notes for the day (e.g., illness, travel, device issues)optional | Ran 10k event |
| Numbers 17 columns | |||
steps | integer | Total number of steps recorded for the user on the given date0 or more · optional | 13221 |
distance_km | float | Total distance in kilometers covered by the user on the given date0 or more · optional | 10.9 |
active_minutes | integer | Total minutes of moderate to vigorous physical activity recorded0 or more · optional | 102 |
calories_burned | float | Total calories burned as estimated by the wearable device0 or more · optional | 889.2 |
resting_heart_rate | integer | Resting heart rate (beats per minute) averaged for the day30 to 120 · optional | 62 |
max_heart_rate | integer | Maximum heart rate (beats per minute) recorded during the day50 to 250 · optional | 168 |
avg_heart_rate | integer | Average heart rate (beats per minute) for the day30 to 220 · optional | 105 |
sleep_duration_minutes | integer | Total sleep duration in minutes for the night preceding the log date0 to 1,440 · optional | 415 |
sleep_efficiency | float | Percentage of time in bed spent asleep (0-100)0 to 100 · optional | 92.4 |
deep_sleep_minutes | integer | Total minutes spent in deep sleep stage0 or more · optional | 97 |
light_sleep_minutes | integer | Total minutes spent in light sleep stage0 or more · optional | 202 |
rem_sleep_minutes | integer | Total minutes spent in REM sleep stage0 or more · optional | 68 |
awake_minutes | integer | Total minutes awake during the sleep period0 or more · optional | 48 |
body_temperature_c | float | Average body temperature in Celsius recorded during the day30 to 45 · optional | 36.7 |
blood_oxygen_percent | float | Average blood oxygen saturation percentage (SpO2) for the day70 to 100 · optional | 98.4 |
stress_level | integer | Daily stress level score as measured by the device (e.g., 0-100 scale)0 to 100 · optional | 17 |
mood_score | integer | Self-reported mood score for the day (e.g., 1-10 scale)1 to 10 · optional | 8 |
| Dates and times 1 column | |||
log_date | date | Calendar date for the activity and biometrics log entry | 2024-04-01 |
Use it for
A healthcare dashboard
Sleep_
efficiency. Excel, Power BI or Tableau. What pattern can you find in 200 rows?
A class exercise
Hand out the rows and one question. Everyone works from the same 200 rows.
- Users200U00192.4U00290.2U00390.9
A software demo
Believable users with log_
date, device_ id and steps to fill a screen in front of a buyer.
This dataset200 rows21 columns
Yours1,000 rows21 columns
blueprint · digital-health-wearable-activity-logs
Behind this dataset
Same schema. As many rows as you need.
These 200 rows came out of a blueprint — 21 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.
Rules it was built with
- Log steps, heart rate, sleep hours
- Each user has unique daily profiles
- Include device type and firmware version
- Omit identifiable user info
Open the blueprint in Data Factory
1 credit per row. Preview 20 rows free. Buy rows for the full run.
- Exports
- CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
- Licence
- yours to use, including commercially
- API slug
- digital-health-wearable-activity-logs