Feasibility of a Sensor-Based Technological Platform in Assessing Gait and Sleep of In-Hospital Stroke and Incomplete Spinal Cord Injury (iSCI) Patients

Sensors, 2020 · DOI: 10.3390/s20102748 · Published: May 12, 2020

Simple Explanation

This study examines the feasibility of using sensors to monitor gait and sleep in patients with stroke and incomplete spinal cord injury (iSCI) within a clinical setting. The sensor-based platform uses inertial measurement units (IMUs) worn on the ankles during the day and a bed sensor placed under the mattress at night to gather data. The results showed that the sensor-based platform is feasible for continuously monitoring gait and sleep of iSCI and stroke patients in a clinical rehabilitation setting.

Study Duration

One week

Participants

25 patients (12 incomplete spinal cord injury (iSCI), 13 stroke)

Evidence Level

Not specified

Key Findings

1
The percentage of missing measurement days and nights was 14% and 4%, respectively, indicating generally good data collection.
2
The main cause of missing measurement days was related to missing data from the inertial measurement unit (IMU) sensors.
3
Participants generally found the sensors easy to use, experienced no discomfort, and were not significantly impeded by wearing them.

Research Summary

This study evaluated the feasibility of a sensor-based technological platform for monitoring gait and sleep in iSCI and stroke patients within a clinical setting. The platform uses IMUs and a bed sensor to collect data continuously, with feasibility assessed based on missing data, error causes, and user experience. The findings suggest that the platform is feasible for clinical use, with low percentages of missing data and positive user feedback, paving the way for further development and implementation.

Practical Implications

Clinical Monitoring

Continuous and objective monitoring of gait and sleep patterns in neurological patients during inpatient rehabilitation.

Personalized Treatment

Potential for optimized and personalized treatment plans based on real-time, patient-specific movement data.

Rehabilitation Progress Tracking

Tracking patients’ progression and evaluation during inpatient rehabilitation.

Study Limitations

1
Not every human interaction error may have been reported, potentially underestimating the percentage of missing measurement days.
2
The study used only one sensor for sleep monitoring.
3
The researchers did not track everything during the protocol.

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