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One-dimensional photonic wave devices exhibit a pivotal role in wave engineering. Despite their relative simplicity, designing 1D wave devices that implement complex functionalities over a broad frequency range is challenging and requires careful sculpting and multiple optimizations. This paper theoretically and experimentally demonstrates a new inverse design paradigm to achieve a desired broadband frequency response efficiently.
View Article and Find Full Text PDFFeasibility of Using a Novel, Multimodal Motor Function Assessment Platform With Machine Learning to Identify Individuals With Mild Cognitive Impairment.
Alzheimer Dis Assoc Disord
November 2024
Department of Physical Therapy.
Introduction: Early identification of clinical conditions associated with Alzheimer disease and related dementias (ADRD) is vital for intervention. One promising early detection method is the use of instrumented assessment to identify subtle motor declines associated with ADRD. This pilot study sought to establish the feasibility of building a machine learning model to identify individuals with mild cognitive impairment (MCI) using motor function data obtained from an inexpensive, portable device.
View Article and Find Full Text PDFVirtual Obstacle Avoidance Strategy: Navigating through a Complex Environment While Interacting with Virtual and Physical Elements.
Sensors (Basel)
September 2024
Graduate Program in Informatics, Federal University of Espírito Santo, Vitória 29075-910, ES, Brazil.
Robotic walking devices can be used for intensive exercises to enhance gait rehabilitation therapies. Mixed Reality (MR) techniques may improve engagement through immersive and interactive environments. This article introduces an MR-based multimodal human-robot interaction strategy designed to enable shared control with a Smart Walker.
View Article and Find Full Text PDFSo I Guess I Am a Device? Making the Case for Professional Practice in the Context of the FDA's Final Rule on Laboratory-Developed Tests.
J Appl Lab Med
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Department of Laboratory Medicine and Pathology, Mayo Clinic Arizona, Phoenix, AZ, United States.
Effective clinical decision support implementation using a multi filter and wrapper optimisation model for Internet of Things based healthcare data.
Sci Rep
September 2024
Department of Computer Science and Engineering, PSN College of Engineering and Technology, Tirunelveli, Tamil Nadu, 627451, India.
Feature Selection (FS) is essential in the Internet of Things (IoT)-based Clinical Decision Support Systems (CDSS) to improve the accuracy and efficiency of the system. With the increasing number of sensors and devices used in healthcare, the volume of data generated is vast and complex. Relevant FS from this data is crucial in reducing computational overhead, improving the system's interpretability, and enhancing the Decision-Making System (DMS) quality.
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