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Magnetized Micropillar-Enabled Wearable Sensors for Touchless and Intelligent Information Communication.

ABSTRACT: The wearable sensors have recently attracted considerable attentions as communication interfaces through the information perception, decoding, and conveying process. However, it is still challenging to obtain a sensor that can convert detectable signals into multiple outputs for convenient, efficient, cryptic, and high-capacity information transmission. Herein, we present a capacitive sensor of magnetic field based on a tilted flexible micromagnet array (t-FMA) as the proposed interaction interface. With the bidirectional bending capability of t-FMA actuated by magnetic torque, the sensor can recognize both the magnitude and orientation of magnetic field in real time with non-overlapping capacitance signals. The optimized sensor exhibits the high sensitivity of over 1.3 T^-1 and detection limit down to 1 mT with excellent durability. As a proof of concept, the sensor has been successfully demonstrated for convenient, efficient, and programmable interaction systems, e.g., touchless Morse code and Braille communication. The distinguishable recognition of the magnetic field orientation and magnitude further enables the sensor unit as a high-capacity transmitter for cryptic information interaction (e.g., encoded ID recognition) and multi-control instruction outputting. We believe that the proposed magnetic field sensor can open up a potential avenue for future applications including information communication, virtual reality device, and interactive robotics.

SUBMITTER: Zhou Q

PROVIDER: S-EPMC8440750 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundEffective communication is the bedrock of quality health care, but it continues to be a major problem for patients, family caregivers, health care providers, and organizations. Although progress related to communication skills training for health care providers has been made, clinical practice and research gaps persist, particularly regarding how to best monitor, measure, and evaluate the implementation of communication skills in the actual clinical setting and provide timely feedback about communication effectiveness and quality.ObjectiveOur interdisciplinary team of investigators aims to develop, and pilot test, a novel sensing system and associated natural language processing algorithms (CommSense) that can (1) be used on mobile devices, such as smartwatches; (2) reliably capture patient-clinician interactions in a clinical setting; and (3) process these communications to extract key markers of communication effectiveness and quality. The long-term goal of this research is to use CommSense in a variety of health care contexts to provide real-time feedback to end users to improve communication and patient health outcomes.MethodsThis is a 1-year pilot study. During Phase I (Aim 1), we will identify feasible metrics of communication to extract from conversations using CommSense. To achieve this, clinical investigators will conduct a thorough review of the recent health care communication and palliative care literature to develop an evidence-based "ideal and optimal" list of communication metrics. This list will be discussed collaboratively within the study team and consensus will be reached regarding the included items. In Phase II (Aim 2), we will develop the CommSense software by sharing the "ideal and optimal" list of communication metrics with engineering investigators to gauge technical feasibility. CommSense will build upon prior work using an existing Android smartwatch platform (SWear) and will include sensing modules that can collect (1) physiological metrics via embedded sensors to measure markers of stress (eg, heart rate variability), (2) gesture data via embedded accelerometer and gyroscope sensors, and (3) voice and ultimately textual features via the embedded microphone. In Phase III (Aim 3), we will pilot test the ability of CommSense to accurately extract identified communication metrics using simulated clinical scenarios with nurse and physician participants.ResultsDevelopment of the CommSense platform began in November 2021, with participant recruitment expected to begin in summer 2022. We anticipate that preliminary results will be available in fall 2022.ConclusionsCommSense is poised to make a valuable contribution to communication science, ubiquitous computing technologies, and natural language processing. We are particularly eager to explore the ability of CommSense to support effective virtual and remote health care interactions and reduce disparities related to patient-clinician communication in the context of serious illness.International registered report identifier (irrid)PRR1-10.2196/37975.

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Magnetized Micropillar-Enabled Wearable Sensors for Touchless and Intelligent Information Communication.

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