Stroke is one of the major causes of disability worldwide, and patients with residual neurological deficits are recommended to undergo rehabilitation. Besides baseline medical conditions, many other factors play a role in rehabilitation success, including patient engagement and medical complications. Wearable technology allows objective and continuous monitoring of body functions and behavior. Furthermore, wearable sensors could detect the risk of adverse events such as falls, infection and mood disorders. In the past, we gained experience using wearable sensors for stroke gait analysis. For example, we have evaluated algorithms to quantify gait patterns using inertial measurement units (IMUs) data and demonstrated that we can quantify and visualize changes in gait patterns in both healthy and stroke populations. As a next step, we aim to combine multiple wearable sensors and data modalities to further assess patient performance in rehabiliation. This planned study aims to investigate the efficacy of wearable devices, including, continuous glucose monitoring (CGM), and smartwatch devices. We will not only investigate the potential of wearable devices in quantifying the improvement in neurological function and reducing complications during the early stroke rehabilitation process, but also assess the effects of using wearables in improving patient engagement and motivation during early stroke rehabilitation.