Using Smartphones to Collect Quantitative Data on Lower Limb Functionality in People Who Have Suffered a Stroke

Area of Science:

• Biomedical Engineering
• Rehabilitation Science
• Digital Health

Background:

• Stroke survivors often experience significant lower limb dysfunction, affecting balance, strength, and mobility.
• Assessing these deficits is crucial for effective rehabilitation and predicting community ambulation.
• Traditional assessment methods can be subjective or require specialized equipment.

Purpose of the Study:

• To utilize smartphone inertial sensors for quantitative assessment of lower limb function in acute stroke patients.
• To evaluate the reliability of smartphone-based data for the Timed Up and Go (TUG) and Sit to Stand (STS) tests.
• To correlate sensor data with functional impairments in stroke survivors.

Main Methods:

• A cross-sectional study involving 8 elderly stroke patients (mean age 67.5 years).
• Participants performed the TUG and STS tests using a smartphone's integrated inertial sensor.
• Quantitative parameters including time, trunk movement, angular displacement, velocity, and acceleration were measured.

Main Results:

• Consistent angular displacement was observed during sitting-to-standing and standing-to-sitting phases (approx. 38°).
• Mean walking velocities during the TUG test were 0.59 m/s (outward) and 0.61 m/s (return).
• High intra- and interobserver reliability (0.860-0.897) was found for sensor-recorded variables.

Conclusions:

• Stroke-related balance and strength deficits necessitate compensatory strategies, reducing walking speed and community mobility.
• Smartphones offer a reliable and accessible tool for quantifying lower limb function in stroke patients.
• Smartphone-based assessments can provide objective data to guide rehabilitation interventions.