Healthcare
18 columns
200 rows
8 formats

Multimodal Healthcare Device Readings

This dataset provides a unified, event-level view of patient health by integrating device telemetry, vital sign measurements, and laboratory results. Each record is timestamped and linked to both patient and device, enabling advanced multimodal AI research, cross-sensor data fusion, and holistic patient state modeling for healthcare analytics and clinical studies.

last updated 22 Jul 2025
by GoMask

The brief that made it

Multimodal AI modeling for patient health state prediction

Sample rows

preview · 8 of 200 rows · all 18 columns

patient_idstring	vital_sign_typestring	vital_sign_valuefloat	sensor_typestring	reading_idstring	timestampdatetime	device_idstring	device_typestring	reading_valuefloat	reading_unitstring	lab_test_namestring	lab_test_resultfloat	lab_test_unitstring	vital_sign_unitstring	location_latitudefloat	location_longitudefloat	reading_statusstring	notesstring
PT-001	blank	blank	heart_rate	RD-10001	2023-03-01T08:17:32	DV-ECG-01	ECG	74	bpm	blank	blank	blank	blank	40.7128	-74.006	valid	Routine ECG check during morning rounds.
PT-002	blank	blank	glucose	RD-10002	2022-12-15T19:22:11	DV-WEAR-04	wearable	142	mg/dL	blank	blank	blank	blank	51.5074	-0.1278	valid	Glucose recorded after light breakfast; normal.
PT-003	blood_pressure_systolic	128	blank	RD-10003	2023-01-06T23:45:19	DV-BPM-07	blood_pressure_monitor	128	mmHg	blank	blank	blank	mmHg	34.0522	-118.2437	valid	Systolic pressure within normal range.
PT-004	blank	blank	blank	RD-10004	2024-01-11T07:31:43	DV-LAB-02	lab_analyzer	13.6	g/dL	hemoglobin	13.6	g/dL	blank	blank	blank	valid	Pre-surgery hemoglobin; within normal range.
PT-005	blank	blank	accelerometer	RD-10005	2023-10-03T06:03:20	DV-WEAR-02	wearable	1.3	g	blank	blank	blank	blank	35.6895	139.6917	valid	Activity monitor showed moderate walking.
PT-006	body_temperature	36.7	temperature	RD-10006	2023-11-22T16:41:18	DV-THERM-01	thermometer	36.7	°C	blank	blank	blank	°C	48.8566	2.3522	valid	No fever detected during evening check.
PT-007	blood_pressure_systolic	142	blank	RD-10007	2023-07-09T13:14:50	DV-BPM-06	blood_pressure_monitor	142	mmHg	blank	blank	blank	mmHg	41.8781	-87.6298	outlier	Elevated systolic pressure; patient reported stress.
PT-008	blank	blank	blank	RD-10008	2023-06-18T00:33:09	DV-LAB-04	lab_analyzer	5.2	mmol/L	creatinine	5.2	mmol/L	blank	blank	blank	outlier	Creatinine elevated; possible renal impairment.
PT-009	blank	blank	temperature	RD-10009	2024-03-05T21:56:13	DV-WEAR-03	wearable	39.2	°C	blank	blank	blank	blank	55.7558	37.6176	outlier	High temperature detected; possible infection.
PT-010	respiratory_rate	24	spirometry	RD-10010	2022-11-28T10:09:25	DV-SPIRO-02	spirometer	0.4	L	blank	blank	blank	breaths/min	52.52	13.405	valid	Pulmonary function test for pediatric patient.
PT-011	blank	blank	blank	RD-10011	2023-05-18T15:23:48	DV-LAB-01	lab_analyzer	0.59	mmol/L	bilirubin	0.59	mmol/L	blank	blank	blank	valid	Newborn screening; bilirubin within normal limits.
PT-012	blank	blank	glucose	RD-10012	2023-09-21T21:18:05	DV-WEAR-01	wearable	61	mg/dL	blank	blank	blank	blank	59.3293	18.0686	outlier	Low glucose detected overnight; hypoglycemia risk.
PT-013	respiratory_rate	38	spirometry	RD-10013	2024-04-07T09:40:45	DV-SPIRO-03	spirometer	3.9	L	blank	blank	blank	breaths/min	blank	blank	outlier	Spirometry value above typical adult range.
PT-014	body_temperature	35	temperature	RD-10014	2023-02-16T03:57:27	DV-THERM-02	thermometer	35	°C	blank	blank	blank	°C	37.7749	-122.4194	outlier	Low body temperature, possible hypothermia.
PT-015	blood_pressure_diastolic	0	blank	RD-10015	2022-10-25T11:49:17	DV-BPM-01	blood_pressure_monitor	0	mmHg	blank	blank	blank	mmHg	-90	180	error	Device error: failed to detect diastolic pressure.
PT-016	blank	blank	blank	RD-10016	2023-08-08T14:12:16	DV-LAB-03	lab_analyzer	blank	blank	cholesterol	blank	mg/dL	blank	blank	blank	missing	Lab sample insufficient; cholesterol not measured.
PT-017	blank	blank	accelerometer	RD-10017	2024-02-13T12:11:03	DV-WEAR-05	wearable	-0.1	g	blank	blank	blank	blank	60.1699	24.9384	error	Calibration issue; negative acceleration detected.
PT-018	blank	blank	heart_rate	RD-10018	2023-12-04T18:39:01	DV-EGC-02	ECG	188	bpm	blank	blank	blank	blank	25.276987	55.296249	outlier	Tachycardia event during exercise session.
PT-019	respiratory_rate	28	spirometry	RD-10019	2024-01-21T04:27:09	DV-SPIRO-01	spirometer	1.2	L	blank	blank	blank	breaths/min	41.3851	2.1734	valid	Routine spirometry for asthmatic child.
PT-020	blood_pressure_systolic	162	blank	RD-10020	2023-04-22T05:58:30	DV-BPM-04	blood_pressure_monitor	162	mmHg	blank	blank	blank	mmHg	35.6762	139.6503	outlier	Critical systolic value; patient referred for evaluation.

What the 200 rows show

from the 200-row sample

Blood_pressure_systolic (vital sign type) stands out: mean vital_sign_value is 140.9, against 47.1 for the rest.

43.0median vital_sign_value
3lab test units
3vital sign units
4lab test names
4reading statuses
6device types

Mean vital_sign_value by vital_sign_type77 rows

vital_sign_value77 rows, in bands of 20

Median 43.0, from 0.0 to 169.0.

sensor_type126 rows with a value · 74 left blank

temperature36
heart_rate26
glucose24
accelerometer20
spirometry20

18 columns by typefrom the column list below

string 12
float 5
datetime 1

Columns

18 columns in three groups

blueprint · 18 columns
column	type	description	example
Text 12 columns
`patient_id`	string	Unique identifier for each patient in the dataset	PT-001
`reading_id`	string	Unique identifier for each reading or event recordunique	RD-10001
`device_id`	string	Unique identifier for the device that captured the reading	DV-ECG-01
`device_type`	string	Type or model of the device (e.g., ECG, blood pressure monitor, wearable)6 types	ECG
`sensor_type`	string	Type of sensor or modality (e.g., heart_rate, temperature, glucose, accelerometer)5 types	heart_rate
`reading_unit`	string	Unit of measurement for the reading value (e.g., bpm, mmHg, °C, mg/dL)8 units	bpm
`lab_test_name`	string	Name of the laboratory test, if applicable (e.g., hemoglobin, cholesterol). Null if not a lab result.4 names · optional	hemoglobin
`lab_test_unit`	string	Unit of the laboratory test result, if applicable. Null if not a lab result.3 units · optional	g/dL
`vital_sign_type`	string	Type of vital sign measured (e.g., blood_pressure_systolic, blood_pressure_diastolic, respiratory_rate). Null if not a vital sign.4 types · optional	blood_pressure_systolic
`vital_sign_unit`	string	Unit of the vital sign value, if applicable. Null if not a vital sign.3 units · optional	mmHg
`reading_status`	string	Status of the reading (e.g., valid, error, missing, outlier)valid · error · missing · outlier	valid
`notes`	string	Free-text notes or comments about the reading, device, or patient contextoptional	Routine ECG check during …
Numbers 5 columns
`reading_value`	float	Measured value from the device or sensor	74
`lab_test_result`	float	Result value of the laboratory test, if applicable. Null if not a lab result.optional	13.6
`vital_sign_value`	float	Value of the vital sign measured, if applicable. Null if not a vital sign.optional	128
`location_latitude`	float	Latitude of the device or patient location at the time of reading, if available-90 to 90 · optional	40.7128
`location_longitude`	float	Longitude of the device or patient location at the time of reading, if available-180 to 180 · optional	-74.006
Dates and times 1 column
`timestamp`	datetime	Date and time when the reading was taken	2023-03-01T08:17:32

Use it for

A healthcare dashboard
Vital_sign_value by vital_sign_type and a breakdown of sensor_type. Excel, Power BI or Tableau.
Why do the 18 blood_pressure_systolic rows have a mean vital_sign_value of 140.9?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Patients200
PT-001—
PT-002—
PT-003128blood_pr…
A software demo
Believable patients with reading_id, timestamp and device_id to fill a screen in front of a buyer.

This dataset200 rows18 columns

Yours1,000 rows18 columnslocation_latitude: UK only

blueprint · multimodal-healthcare-device-readings

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 18 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

Vital signs have periodicity
Lab results have time delay post-order
Device malfunctions flagged and logged
Patient alerts triggered at threshold breaches
Data synchronized across sources

Rows1,000 rows10,000 rows100,000 rows1,000,000 rows

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: multimodal-healthcare-device-readings

What should your data show?

No signup. No card.

Sample rows

What the 200 rows show

Columns

Use it for

A healthcare dashboard

A root-cause class exercise

A software demo

Make it yours.

Same schema. As many rows as you need.

More in Healthcare

What should your data show?