im going to give you what i think is accurate but im not completely sure, The integration of wearable sensors, such as Inertial Measurement Units (IMUs), for gait analysis in neurorehabilitation is a rapidly advancing field, but its adoption remains uneven. Primary Drivers: Objectivity & Quantification: Wearables provide objective, quantitative data on movement patterns (e.g., gait speed, symmetry, joint angles), moving beyond subjective clinical observation. Continuous, Real-World Monitoring: They enable assessment outside the lab in a patient's natural environment, offering a more complete picture of their functional capacity and daily activity. Patient Engagement: Real-time feedback and progress tracking can enhance patient motivation and adherence to rehabilitation programs. Key Challenges to Adoption: Cost and Accessibility: The expense of hardware, software, and maintenance can be prohibitive, especially in low-resource settings. Technical Expertise: Clinicians require specialized training to operate the systems, interpret the complex data, and troubleshoot technical issues. Data Standardization: A lack of consensus on data processing protocols and key outcome metrics makes it difficult to compare results across studies and clinical sites. Current Evidence and Feasibility: The strongest evidence for improved outcomes is currently in stroke rehabilitation, where sensors have been shown to increase the accuracy of assessment. Feasibility varies dramatically between high-resource clinical centers, which may have dedicated biomechanics staff, and low-resource settings, where infrastructural and training gaps are significant barriers.

First, the theory; then, the experiment! The ideomotor approach has proven helpful in the neurocognitive study of conscious bodily movements. "Anticipation," based on stored effects of actions, plays a central role in not only motor commands leading to biomechanically measurable events, but also in providing a picture of evaluated effects in terms of afferent signals. This "picture" appears to be necessary for integrating signals from wearables. What good is all the additional information if the researcher doesn't know how the brain integrates, stores it, to the benefit of next action effects? The ideomotor approach examines how thoughts and ideas unconsciously influence movements.

"Anticipation" refers to the brain's ability to predict future events based on past experiences.

Hello. In our hospital, we are trying to analyze and monitor patients’ movements using their own smart devices. The biggest obstacle we have encountered is the technology itself. Exporting data across all available devices (most often Apple, Android, and Garmin) is not that simple. After some time, we managed to develop our own program that is capable of doing this, which allows us to monitor whether patients are following our movement recommendations or not. We are now conducting a smaller study that specifically evaluates this data.