# Evaluating the Feasibility of Euler Angles for Bed-Based Patient Movement Monitoring
###### Abstract  
In the field of modern healthcare, technology plays a crucial role in improving patient care and ensuring their safety. One area where advancements can still be made is in alert systems, which provide timely notifications to hospital staff about critical events involving patients. These early warning systems allow for swift responses and appropriate interventions when needed. A commonly used patient alert technology is nurse call systems, which empower patients to request assistance using bedside devices. Over time, these systems have evolved to include features such as call prioritization, integration with staff communication tools, and links to patient monitoring setups that can generate alerts based on vital signs. There is currently a shortage of smart systems that use sensors to inform healthcare workers about the activity levels of patients who are confined to their beds. Current systems mainly focus on alerting staff when patients become disconnected from monitoring machines. In this technical note, we discuss the potential of utilizing cost-effective sensors to monitor and evaluate typical movements made by hospitalized bed-bound patients. To improve the care provided to unaware patients further, healthcare professionals could benefit from implementing trigger alert systems that are based on detecting patient movements. Such systems would promptly notify mobile devices or nursing stations whenever a patient displays restlessness or leaves their bed urgently and requires medical attention. bed-based movement; detection; monitoring; Euler angles +
Footnote †: journal: MedicalSimilar to physiological monitoring devices, the aforementioned technologies employ a comparable approach. They constantly keep track of crucial signs like heart rate, blood pressure, respiratory rate, and oxygen saturation. Even minor fluctuations in these vital signs can indicate the presence of a life-threatening event when they occur within 24 h prior [4]. As a result, these devices can be programmed to produce alarms or notifications when certain thresholds are surpassed or specific patterns are identified. This has the potential to enable early detection of patient deterioration during hospitalization so that healthcare professionals can intervene promptly [5]. Along with patient-operated devices and physiological monitors, centralized alert systems are also available. These systems gather information from multiple sources, including monitoring devices and electronic health records, to create comprehensive alerts. By utilizing algorithms and rules, they analyze the data and detect critical events or unusual patterns. The identified issues are then communicated to relevant healthcare personnel for prompt action. Different alert systems have been studied before, including alarms that notify caregivers when a patient tries to get out of bed without help [6]. These alarms are effective but need to be part of a larger plan for preventing falls. However, thanks to technological advancements, there are now more advanced options available, such as wearable devices and smart sensors placed discreetly on or near patients, for real-time monitoring while causing minimal disruption or interference. As anticipated, there is currently a lack of sensor-based smart systems that notify healthcare staff about the activity levels of bed-ridden patients. Existing systems primarily focus on alerting staff when patients become disconnected from monitoring machines. Therefore, in this 'technical note', we present the possibility of using affordable sensors to monitor common movements experienced by hospital-bed-bound patients and assess their feasibility. A unique approach that utilizes sensors to track a patient's body positions and movements while they are in bed can serve as an effective solution. This technology not only allows for quick responses but also ensures the safety and well-being of patients without disrupting their sleep, thereby improving the overall quality of care provided.