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Helpful Places

Government of Canada – DTPR AI Register

AI-Powered Fatigue and Stress Detection via Biosensors

Healthcare · Employment & Work

What it collects that can identify you

Biometric
Pseudonymous data
  • Biosensor readings from GC employees, including physiological signals used to infer fatigue and stress (e.g., heart rate variability, galvanic skin response, or similar wearable sensor data).
Sensitive personal information
Pseudonymous data
  • Health database records and de-identified datasets containing physiological and health-related data used to train and operate the fatigue and stress detection algorithms.
Run by
Canadian Space Agency (CSA)
Where
No fixed location
Kept
Not stated by the Helpful Places.
Shared with
Accountable organization
Your copy
You cannot see the data it holds about you. What you can do

What it is for

HealthcareEmployment & Work

This system uses machine learning and deep learning algorithms to monitor and detect fatigue and stress in Government of Canada employees through biosensor data. It is currently under development by Myant, a vendor contracted by the Canadian Space Agency. The system processes health-related personal information from individuals, and users are informed of AI use. Personal data is drawn from health databases and de-identified datasets.

What it collects and what happens to it

Data taken in

Biometric
Pseudonymous data
  • Biosensor readings from GC employees, including physiological signals used to infer fatigue and stress (e.g., heart rate variability, galvanic skin response, or similar wearable sensor data).
Sensitive personal information
Pseudonymous data
  • Health database records and de-identified datasets containing physiological and health-related data used to train and operate the fatigue and stress detection algorithms.

Processing

Classification & Prediction
  • Machine learning and deep learning models classify fatigue and stress levels from biosensor time-series data. The system uses trained neural networks to detect physiological patterns indicative of fatigue or stress states.

What it does

Sensing (Perceptive AI)
Human decides
  • The system senses physiological signals from biosensors worn by employees and converts them into structured detections of fatigue and stress states.
Deciding (Analytical AI)
Human decides
  • The system classifies and scores fatigue and stress levels from biosensor inputs using machine learning and deep learning models, producing alerts or status classifications for human review.

Outputs

A recommendation or prediction
Pseudonymous data
  • The system produces fatigue and stress status scores or alerts derived from biosensor data, intended to be reviewed by GC employees or supervisors rather than to trigger automatic actions.

Run by

Canadian Space Agency (CSA)
  • The Canadian Space Agency is the Government of Canada department accountable for deploying this fatigue and stress detection system for use by GC employees.

GC AI Register — 2526-CSA-ASC-003

Built by

Myant
  • Myant is the vendor that developed the fatigue and stress detection algorithms under contract with the Canadian Space Agency.

GC AI Register — 2526-CSA-ASC-003

Kept for

Not stated by the Helpful Places.

Shared with

Not available to me
  • The source material does not describe a mechanism for individual employees to directly access their own fatigue and stress data produced by this system.
Available to the accountable organization
  • Output data from the fatigue and stress detection system is available to the Canadian Space Agency as the accountable organization. The scope of access within the organization is not specified in the source material.

Stored

Not stated by the Helpful Places.

How to read the colours

Can it identify you?

Anonymized data
Data about people with the link to who is broken. Stripped of identifiers, blurred, aggregated, or noised so this system can’t reasonably tie a record back to an individual.
Pseudonymous data
Each person’s data is tied to a token (hash, ID, template) that lets this system recognise the same person across events, but the token itself doesn’t reveal a name. Reidentification is possible with extra information.
Identifiable data
The data either contains a direct identifier (name, address, account name, recognisable face or voice, plate number) or carries a token this system uses to look up legal identity during processing.

Who completes the loop?

Human decides
This mode suggests; a person decides what to do next. The AI is always advisory — a human is in the loop on every decision. Example: a triage tool ranks cases for a clinician who chooses which to see first.
Human executes
This mode decides; a person carries out the result. Example: an optimizer plans the day’s trash-collection routes, and drivers run them.
Autonomous
This mode decides and acts on its own. No person reviews each decision or carries out the resulting action.

Definitions from the DTPR standard. Amber is about your data, violet about who decides. The fuller the shape and the deeper the colour, the more identifying the data or the less a person is involved.

What you can do

Ask about this system

Questions go to the Helpful Places, not the vendor.

Your rights

  • Right to Be Informed of AI UseGC employees are informed that an AI system is in use. The register confirms AI use is disclosed to users. Contact the Canadian Space Agency for further information about how disclosure is made in practice.
  • Right to Algorithmic TransparencyAs a Government of Canada AI system, employees may request information about how this system works under the Access to Information Act or through the Canadian Space Agency. The system is listed in the GC AI Register at open.canada.ca.

Risks and safeguards

  • Psychological harmContinuous biometric monitoring of employees for fatigue and stress may create anxiety, a chilling effect on natural behaviour, or distress if results are used in performance evaluation. The register indicates AI use is disclosed to users; however, no further mitigations (such as opt-out mechanisms, limitations on managerial access to results, or independent oversight) are described in the available source material.
  • Civil liberties harmWorkplace biosensor monitoring raises concerns about employee autonomy and freedom from surveillance, particularly if data is shared with managers or used in disciplinary processes. The source material states personal information is involved and AI use is disclosed, but provides no detail on access controls, purpose limitations, or consent mechanisms that would protect civil liberties.