Exploring unsupervised feature extraction of IMU-based gait data in stroke rehabilitation using a variational autoencoder.

Background: Variational AutoEncoders (VAE) might be utilized to extract relevant information from an IMU-based gait measurement by reducing the sensor data to a low-dimensional representation. The present study explored whether VAEs can reduce IMU-based gait data of people after stroke into a few latent features with minimal reconstruction error. Additionally, we evaluated the psychometric properties of the latent features in comparison to gait speed, by assessing 1) their reliability; 2) the difference in scores between people after stroke and healthy controls; and 3) their responsiveness during rehabilitation.

Reliability parameters of the Timed 25-Foot-Walk (T25FW) in patients with Multiple Sclerosis: Lower walking speed is associated with greater Smallest Detectable Change.

Background: Reliability parameters of clinical measures should be sufficient in order to adequately monitor disease course and evaluate treatment in patients with Multiple Sclerosis (MS). The aim of this study was to assess the reliability of the Timed 25-Foot-Walk (T25FW) in patients with MS.

Methods: MS patients performed the T25FW twice with approximately one year in between.

Beyond gait speed: exploring the added value of Inertial Measurement Unit-based measurements of gait in the estimation of the walking ability in daily life.

Background: Gait speed is often used to estimate the walking ability in daily life in people after stroke. While measuring gait with inertial measurement units (IMUs) during clinical assessment yields additional information, it remains unclear if this information can improve the estimation of the walking ability in daily life beyond gait speed.

Objective: We evaluated the additive value of IMU-based gait features over a simple gait-speed measurement in the estimation of walking ability in people after stroke.

Predicting Recovery of Independent Walking After Stroke: A Systematic Review.

Patients recovering from a stroke experience reduced participation, especially when they are limited in daily activities involving walking. Understanding the recovery of independent walking, can be used by clinicians in the decision-making process during rehabilitation, resulting in more personalized stroke rehabilitation. Therefore, it is necessary to gain insight in predicting the recovery of independent walking in patients after stroke.

Reliability of IMU-based balance assessment in clinical stroke rehabilitation.

Background: Balance is often affected after stroke, severely impacting activities of daily life. Conventional testing methods to assess balance provide limited information, as they are subjected to floor and ceiling effects. Instrumented tests, for instance using inertial measurement units, offer a feasible and promising alternative.