Sensor Data Requirements

ParaDigMa is designed for analysis of wrist-worn sensor data collected during passive monitoring in persons with Parkinson’s disease. This guide specifies the sensor and data requirements for each pipeline.

General Requirements

All pipelines require data from a wrist-worn sensor with:

Sensor Position: Either wrist (left or right)
Population: Persons with Parkinson’s disease
Data Quality: Strictly increasing timestamps
Orientation: Standardized coordinate system (see Coordinate System Guide)

Pipeline-Specific Requirements

Arm Swing during Gait

Sensor Specifications

Specification	Minimum Requirement
Accelerometer	Sampling rate ≥ 100 Hz Range ≥ ± 4 g
Gyroscope	Sampling rate ≥ 100 Hz Range ≥ ± 1000 degrees/sec

Physical Units

Accelerometer: g (gravitational force)
Gyroscope: deg/s (degrees per second)

ParaDigMa has functionalities for converting accelerometer and gyroscope in other units (e.g., m/s^2, rad/s) to these standard units. This can also be setup when using run_paradigma.

Data Compliance

For reliable weekly measures:

Minimum 3 compliant days with ≥10 hours of data between 8 am and 10 pm
At least 2 minutes of arm swing activity per week

Population Constraints

No walking aid usage
No severe dyskinesia in the watch-sided arm

Required Parameters

watch_side: Must specify 'left' or 'right'

Tremor

Sensor Specifications

Specification	Minimum Requirement
Gyroscope	Sampling rate ≥ 100 Hz Range ≥ ± 1000 degrees/sec

Physical Units

Gyroscope: deg/s (degrees per second)

ParaDigMa has functionalities for converting gyroscope in other units (e.g., rad/s) to these standard units. This can also be setup when using run_paradigma.

Data Compliance

For reliable weekly measures:

Minimum 3 compliant days with ≥10 hours of data between 8 am and 10 pm

Pulse Rate

Sensor Specifications

Specification	Minimum Requirement
PPG (Photoplethysmography)	Sampling rate ≥ 30 Hz Green LED wavelength
Accelerometer (optional)	Sampling rate ≥ 100 Hz Range ≥ ± 4 g (for motion artifact detection)

Physical Units

PPG: Blood volume pulse in arbitrary units (device-dependent)
Accelerometer: g (gravitational force) - if used for motion detection

Data Compliance

For reliable weekly measures:

Minimum 12 hours of data per day on average

Population Constraints

No cardiac rhythm disorders (e.g., atrial fibrillation, atrial flutter)

Important Notes

Device-Specific Adaptation: The PPG processing pipeline is currently validated with the blood volume pulse (BVP) signal from the Verily Study Watch. To use PPG data from other devices, see the Pulse Rate Analysis Tutorial for signal adaptation guidance.

Cannot Combine with Other Pipelines: The pulse rate pipeline requires different sensor data (PPG) than gait/tremor (IMU) and must be run separately.

Multi-Pipeline Processing

ParaDigMa supports running compatible pipelines together:

from paradigma.orchestrator import run_paradigma

# Gait and tremor can run together (both use IMU data)
results = run_paradigma(
    dfs=df,
    pipelines=['gait', 'tremor'],
    watch_side='left'
)

Pipeline Compatibility Matrix

Pipeline Combination	Compatible	Reason
Gait + Tremor	✓	Both use IMU sensors (accelerometer + gyroscope)
Gait + Pulse Rate	✗	Different sensor types (IMU vs PPG)
Tremor + Pulse Rate	✗	Different sensor types (IMU vs PPG)
Gait + Tremor + Pulse Rate	✗	Cannot mix IMU and PPG pipelines

Important Notes on Validation

[!NOTE] The specifications above represent minimally validated requirements. For example, while ParaDigMa works with accelerometer and gyroscope data sampled at 50 Hz, the effect on processing accuracy has not been empirically validated. Higher sampling rates and sensor ranges generally improve accuracy.