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An integral part of patient care and recovery involves monitoring patient behavior and understanding their movements in their rooms. Ouva utilizes AI models to break down these movements into specific categories, providing an accurate measure of each patient's mobility.

Interpreting Different Movements

Ouva's AI capability allows it to discern whether a patient is in bed, taking a few steps, or sitting down. This provides medical personnel with a comprehensive overview of their patient's activity and behavior within their room.

Record of Time Spent in Bed

By keeping track of the duration a patient spends resting or sleeping in the bed, Ouva contributes to the assessment of patients' sleep patterns and quality. This is crucial in establishing effective treatment regimens and improving patient well-being.

Observing Unusual Activity Patterns

Detecting anomalies such as reversed day-night activity patterns is another capability of Ouva. Such shifts could indicate worsening health conditions or the onset of delirium, especially among high-risk patients. Early intervention becomes possible with these insights, enhancing patient care.

Developing Mobility Programs

By detailing both the amount and type of physical activity of patients, Ouva aids in the development of tailored patient mobility programs. Such programs can be vital for encouraging early recovery, essentially providing a roadmap towards quicker convalescence and improved patient outcomes.

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