Healthcare
15 columns
200 rows
8 formats

Remote Patient Monitoring Signals

This dataset provides synthetic, multi-modal sensor records for remote patient health monitoring, combining vital signs, device metadata, patient demographics, text logs, and device images. It is ideal for developing machine learning models to detect health anomalies, predict patient needs, and enable real-time alert systems for telehealth and clinical research.

last updated 20 Aug 2025
by GoMask

The brief that made it

Machine learning for health anomaly detection

Sample rows

preview · 8 of 200 rows · all 15 columns

record_idstring	patient_genderstring	patient_ageinteger	alert_flagboolean	signal_unitstring	patient_idstring	timestampdatetime	sensor_typestring	signal_valuefloat	device_idstring	device_locationstring	text_logstring	alert_typestring	patient_conditionstring	image_urlstring
A1B2C3D4E5	female	32	false	%	PAT001	2024-06-12T08:12:43Z	pulse_oximeter	97.2	DEV-0001	finger	Routine check, oxygen normal.	blank	asthmatic	blank
F6G7H8J9K1	female	24	false	°C	PAT002	2024-06-12T08:14:21Z	thermometer	36.7	DEV-0002	oral	Morning temperature, within range.	blank	healthy	blank
M2N3P4Q5R6	male	47	false	bpm	PAT003	2024-06-12T08:17:03Z	ECG	73	DEV-0003	chest	Stable heart rate recorded.	blank	cardiac	blank
S7T8U9V0W1	male	54	false	mmHg	PAT004	2024-06-12T08:20:15Z	blood_pressure	118	DEV-0004	upper_arm	Blood pressure check, normal.	blank	hypertensive	blank
X2Y3Z4A5B6	female	69	false	g	PAT005	2024-06-12T08:23:41Z	accelerometer	0.8	DEV-0005	waist	Low activity detected in early morning.	blank	elderly	blank
C7D8E9F0G1	female	1	true	°C	PAT006	2024-06-12T08:29:18Z	thermometer	38.9	DEV-0006	rectal	Fever detected, monitoring closely.	high_temperature	premature_infant	blank
H2I3J4K5L6	male	68	true	%	PAT007	2024-06-12T08:36:54Z	pulse_oximeter	82.4	DEV-0007	toe	Oxygen low, alert triggered.	low_oxygen	COPD	blank
M7N8O9P0Q1	unknown	101	false	blank	PAT008	2024-06-12T08:42:12Z	camera	blank	DEV-0008	ceiling	Device image captured for monitoring.	blank	experimental	https://remote-med-images.com/dev0008/20240612_084212.jpg
R2S3T4U5V6	male	56	true	bpm	PAT009	2024-06-12T08:49:03Z	ECG	180	DEV-0009	chest	Tachycardia detected, immediate action required.	high_heart_rate	atrial_fibrillation	blank
W7X8Y9Z0A1	male	66	true	mmHg	PAT010	2024-06-12T08:52:36Z	blood_pressure	200	DEV-0010	upper_arm	Critical hypertension, alert triggered.	other	hypertensive	blank
B2C3D4E5F6	other	43	false	°C	PAT011	2024-06-12T08:55:19Z	thermometer	35.1	DEV-0011	armpit	Low temperature recorded, monitoring.	blank	post_surgery	blank
G7H8I9J0K1	female	27	false	%	PAT012	2024-06-12T09:01:43Z	pulse_oximeter	99	DEV-0012	earlobe	Oxygen saturation excellent.	blank	healthy	blank
L2M3N4O5P6	female	80	true	g	PAT013	2024-06-12T09:05:18Z	accelerometer	5.7	DEV-0013	ankle	Sudden movement detected, possible fall.	fall_detected	paralysis	blank
Q7R8S9T0U1	unknown	102	false	custom_unit	PAT014	2024-06-12T09:12:52Z	other	9999.9	DEV-0014	implant	Experimental sensor calibration.	blank	experimental	blank
V2W3X4Y5Z6	male	76	false	blank	PAT015	2024-06-12T09:15:19Z	camera	blank	DEV-0015	bedside	Image captured for patient monitoring.	blank	elderly	https://remote-med-images.com/dev0015/20240612_091519.jpg
A2B3C4D5E6	male	59	true	bpm	PAT016	2024-06-12T09:21:32Z	ECG	0	DEV-0016	chest	No heart rate detected, alert triggered.	high_heart_rate	cardiac	blank
F2G3H4J5K6	female	38	false	°C	PAT017	2024-06-12T09:26:41Z	thermometer	36.2	DEV-0017	oral	Temperature within normal range.	blank	diabetic	blank
M3N4P5Q6R7	male	44	false	mmHg	PAT018	2024-06-12T09:31:52Z	blood_pressure	95	DEV-0018	upper_arm	Low blood pressure noted.	blank	cardiac	blank
S3T4U5V6W7	female	35	false	g	PAT019	2024-06-12T09:37:08Z	accelerometer	1.1	DEV-0019	wrist	Movement detected, patient active.	blank	rehab	blank
X3Y4Z5A6B7	female	3	true	%	PAT020	2024-06-12T09:43:27Z	pulse_oximeter	53.7	DEV-0020	nose	Critically low oxygen detected.	low_oxygen	premature_infant	blank

What the 200 rows show

from the 200-row sample

Unknown (patient gender) stands out: mean patient_age is 97.2, against 49.0 for the rest.

32%alert_flag = true
54median patient_age
5alert types
8sensor types
15patient conditions
16device locations

Mean patient_age by patient_gender200 rows

patient_age200 rows, in bands of 20

Median 54, from 0 to 120.

signal_unit183 rows with a value · 17 left blank

%42
°C37
mmHg33
g30
bpm27
units8
custom_unit6

15 columns by typefrom the column list below

string 11
integer 1
float 1
datetime 1
boolean 1

Columns

15 columns in four groups

blueprint · 15 columns
column	type	description	example
Text 11 columns
`record_id`	string	Unique identifier for each monitoring recordunique	A1B2C3D4E5
`patient_id`	string	Unique identifier for the patient	PAT001
`sensor_type`	string	Type of sensor used to capture the signal (e.g., ECG, pulse oximeter, accelerometer)7 values	pulse_oximeter
`signal_unit`	string	Unit of measurement for the signal value (e.g., bpm, %, mmHg, °C)7 units · optional	%
`device_id`	string	Unique identifier for the monitoring deviceoptional	DEV-0001
`device_location`	string	Physical location of the device (e.g., wrist, chest, bedside)optional	finger
`text_log`	string	Free-text log or annotation from device or patient (e.g., symptoms, notes, alerts)optional	Stable heart rate.
`image_url`	string	URL or path to the device image captured at the time of recordingoptional	https://remote-med-images…
`alert_type`	string	Type of alert triggered (e.g., high_heart_rate, low_oxygen, fall_detected)5 values · optional	high_temperature
`patient_gender`	string	Gender of the patientmale · female · other · unknown · optional	female
`patient_condition`	string	Known medical condition or risk group of the patient (e.g., cardiac, diabetic, elderly)optional	asthmatic
Numbers 2 columns
`signal_value`	float	Primary numeric value recorded by the sensor (e.g., heart rate, SpO2, temperature)0 or more · optional	97.2
`patient_age`	integer	Age of the patient at the time of recording0 to 120 · optional	32
Dates and times 1 column
`timestamp`	datetime	Date and time when the signal was recorded	2024-06-12T08:12:43Z
True or false 1 column
`alert_flag`	boolean	Indicates if the record triggered an alert or anomaly detectionoptional	false

Use it for

A healthcare dashboard
The alert_flag rate, patient_age by patient_gender and a breakdown of signal_unit. Excel, Power BI or Tableau.
Why do the 19 unknown rows have a mean patient_age of 97.2?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Records200
A1B2C3D4E532female
C7D8E9F0G11female
H2I3J4K5L668male
A software demo
Believable records with patient_id, timestamp and sensor_type to fill a screen in front of a buyer.

This dataset200 rows15 columns

Yours1,000 rows15 columnsdevice_location: UK only

blueprint · remote-patient-monitoring-signals

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 15 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

Each record must include time-series sensor readings
Patient ID anonymized for privacy
Include medical device image reference per entry
Text notes must reflect patient symptoms
Missing data patterns must reflect real-world hospital rates

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: remote-patient-monitoring-signals

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?