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Sensor data to monitor a person's health

Measurements, such as heart rate or steps, that a device like a wearable records automatically at regular intervals. It is quantitative data and can reveal a person's health trends.

Part of: VCE Applied Computing - U1O1 - Data analysis — Module 9, ACARA Digital Technologies Years 7–8 — Digital Footprints and Data Minimisation — Module 16, ACARA Digital Technologies Years 9–10 — Acquiring and Validating Data — Module 33, QCE Digital Solutions Unit 1 — Understanding Digital Problems — Module 23

Understanding Sensor data to monitor a person's health in VCE Data Analysis

What it does: The device collects a steps reading every 60 seconds with no user input, which is automatic collection at regular intervals. Combining readings over a week shows a pattern in the person's health, such as how well they are sleeping, which is a health trend. Wearable sensors record measurements automatically, so the user does not need to enter the values. Steps are a measurement recorded by a sensor. They are numbers, so they are quantitative data. Heart rate is a numerical measurement (for example 72 beats per minute), so it is quantitative. Collecting at regular intervals builds a record. Patterns, such as a rising resting heart rate, only appear over time.

Common mistakes: Heart rate from a sensor is quantitative data, so it must be stored as a number such as 72, not as a word like 'fast'. A step count adds each new reading to the running total, so it should be steps + reading, not subtract.

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Learning
Duo
A smartwatch records your heart rate every few seconds without you typing anything. What kind of data collection is this?
Automatic collection by a sensorManual collection by a survey
Matches
Heart rate sensor data is qualitative because a device collects it
↓
Sensor readings such as heart rate are numbers, so they are quantitative data. How the data is collected does not change its type.
Applying
Meanings
Term
sensor data
Meaning
Measurements, such as heart rate or steps, that a device like a wearable records automatically at regular intervals. It is quantitative data and can reveal a person's health trends.
Practice
Time,Heart rate (bpm),Steps
Testing
Gaps
=(B2:B25)
Check Answer
Spots
1sensor ← Wearable
2heart_rate ← 'fast'

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Quick Questions

1. A smartwatch records your heart rate every few seconds without you typing anything. What kind of data collection is this?
A. Automatic collection by a sensor ✓
B. Manual collection by a survey
Wearable sensors record measurements automatically, so the user does not need to enter the values.
2. Which of these is an example of sensor data from a wearable?
A. 8,432 steps recorded in one day ✓
B. A written comment about how you feel about exercise
Steps are a measurement recorded by a sensor. They are numbers, so they are quantitative data.
3. Heart rate readings from a fitness tracker are which type of data?
A. Quantitative data ✓
B. Qualitative data
Heart rate is a numerical measurement (for example 72 beats per minute), so it is quantitative.
4. A wearable saves a heart rate reading every 5 minutes all day. Why is this useful for health monitoring?
A. One reading is enough to show a long-term trend
B. Regular readings can show trends over time ✓
Collecting at regular intervals builds a record. Patterns, such as a rising resting heart rate, only appear over time.
5. Which statement about sensor data is true?
A. Health sensor data is never personal because a device collects it
B. Health sensor data can be personal and sensitive information ✓
Data linked to a person's health is personal data, and health information is sensitive information, so it needs extra protection.

Match the Pairs

sensor data → Measurements such as heart rate or steps that a wearable records automatically at regular intervals
heart_rate = 72 → A quantitative sensor reading, in beats per minute, recorded by a wearable
A wearable records a reading automatically at regular intervals → record(steps, every 60 seconds)
Sensor readings compared over several days can show a health trend → average(sleep_hours, last 7 days)
Heart rate sensor data is qualitative because a device collects it → Sensor readings such as heart rate are numbers, so they are quantitative data. How the data is collected does not change its type.
Wearable heart rate data is not personal because no name is typed in → Sensor data is linked to one person's account or device, so it is personal and can be sensitive health information. It needs protecting.

Key Term

sensor data
Measurements, such as heart rate or steps, that a device like a wearable records automatically at regular intervals. It is quantitative data and can reveal a person's health trends.

Fill in the Blanks

1. =AVERAGE(B2:B25)
Hint: Type the function that finds the mean of the heart rate readings in B2:B25.
2. =MAX(B2:B25)
Hint: Type the function that returns the highest heart rate reading recorded by the wearable.
3. =COUNTIF(B2:B25,">100")
Hint: Type the comparison operator that counts readings above 100 beats per minute.
4. WHILE watchOn = TRUE heartRate ← ReadSensor() END WHILE
Hint: Type the keyword that repeats the sensor reading for as long as the watch is switched on.
5. heartData ← ENCRYPT(heartData)
Hint: Type the function name that scrambles sensitive health data so only authorised users can read it.

Spot the Error

Question 1
A sensor ← Wearable
B heart_rate ← 'fast'
C unit ← 'bpm'
Line B — Heart rate from a sensor is quantitative data, so it must be stored as a number such as 72, not as a word like 'fast'.
Question 2
A steps ← 0
B FOR EACH minute IN hour
C steps ← steps - reading
D OUTPUT steps
Line C — A step count adds each new reading to the running total, so it should be steps + reading, not subtract.
Question 3
A interval ← 'sometimes'
B WAIT interval seconds
C RECORD heart_rate
Line A — Sensors record automatically at regular intervals, so the interval must be a fixed number such as 60, not a vague word.
Question 4
A total ← 0
B FOR EACH hr IN hrs
C total ← total + hr
D avg ← total * COUNT(hrs)
Line D — An average is the total divided by the number of readings, so it should use / and not *.
Question 5
A FOR EACH day IN week
B hr ← GET resting_hr(day)
C APPEND 'good' TO trend
D OUTPUT trend
Line C — A health trend is built from the numeric readings so changes can be compared. It should append hr, not the text 'good'.

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