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Background: Older individuals frequently experience reversible "frailty syndrome,", increasing incidence of disability. Although physical exercise interventions may delay functional decline, there are difficulties in implementing them and performing seamless follow-up at home. Very few technological solutions attempt to address this challenge and improve individual participation.
Objective: Our objectives are to (1) develop a technological solution designed to support active aging of frail older persons, (2) conduct a first laboratory evaluation of the device, and (3) design a multidimensional clinical trial to validate our solution.
Methods: We conducted a first phase of multidisciplinary meetings to identify real end users and health professional's unmet needs, and to produce specifications for the architecture of the solution. In a second phase, we performed laboratory tests of the first proposed prototype (a smart insole) with 3 healthy volunteers. We then designed an ongoing clinical trial to finalize the multidimensional evaluation and improvement of the solution.
Results: To respond to the needs expressed by the stakeholders (frailty monitoring and adherence improvement), we developed a prototype of smart shoe insole to monitor key parameters of frailty during daily life and promote walking. It is a noninvasive wireless insole, which automatically measures gait parameters and transmits information to a remote terminal via a secure Internet connection. To ensure the solution's autonomy and transparency, we developed an original energy harvesting system, which transforms mechanical energy produced by the user's walking movement into electrical energy. The first laboratory tests of this technological solution showed good reliability measures and also a good acceptability for the users. We have planned an original iterative medical research protocol to validate our solution in real life.
Conclusions: Our smart insole could support preventive strategies against disability in primary care by empowering the older patients without increasing the busy health professional's workload.
Trial Registration: Clinicaltrials.gov NCT02316600; https://clinicaltrials.gov/ct2/results?term=NCT02316600&Search=Search. Accessed: 2015-05-13 . (Archived by WebCite at http://www.webcitation.org/6YUTkObrQ).
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http://dx.doi.org/10.2196/rehab.4084 | DOI Listing |
Med Pharm Rep
October 2024
1st Surgery Clinic, Faculty of Medicine, "Vasile Goldis" West University, Arad, Romania.
Diabetic foot ulcers represent a serious and costly complication of diabetes, with significant morbidity and mortality. The purpose of this study was to explore advancements in Artificial Intelligence, and wearable technologies for the prevention and management of diabetic foot ulcers. Key findings indicate that Artificial Intelligence-driven predictive analytics can identify early signs of diabetic foot ulcers, enabling timely interventions.
View Article and Find Full Text PDFCureus
August 2024
Incubation Center, Shriram institute for Industrial Research, Gurugram, IND.
Background Gait analysis has evolved through many years of research. Many methods are used to analyze the gait of a subject. Recent times have shown a high demand for wearable sensor-based insoles integrated with smartphone-based devices used for gait analysis due to ease of use.
View Article and Find Full Text PDFSensors (Basel)
September 2024
Graduate Program in Neuroengineering, Edmond and Lily Safra International Institute of Neuroscience, Macaíba 59280-000, RN, Brazil.
This study presents an IoT-based gait analysis system employing insole pressure sensors to assess gait kinetics. The system integrates piezoresistive sensors within a left foot insole, with data acquisition managed using an ESP32 board that communicates via Wi-Fi through an MQTT IoT framework. In this initial protocol study, we conducted a comparative analysis using the Zeno system, supported by PKMAS as the gold standard, to explore the correlation and agreement of data obtained from the insole system.
View Article and Find Full Text PDFGait Posture
October 2024
Department of Orthopaedic Surgery, Teikyo University Mizonokuchi Hospital, Kanagawa, Japan. Electronic address:
ACS Appl Mater Interfaces
September 2024
State Key Laboratory of Solid Lubrication, Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences, Lanzhou 730000, China.
As an emerging high-efficiency energy conversion device, improving the output of triboelectric nanogenerators (TENGs) is still a key method to promote practical application of TENGs. This paper systematically investigated the influence of component composition, thickness, and surface morphology of the metal conducting layer on the performance of triboelectric nanogenerators. It has been established that these three factors have a significant influence on the output performance of TENGs.
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