Objectives: To evaluate the validity and reliability of a smartphone-based application against inertial sensors to measure head repositioning (by using joint position sense -JPS) and cervical range of motion (ROM).
Methods: JPS and cervical ROM were evaluated for neck flexion, extension and both-sides lateral flexion in thirty-one volunteers. Participants were simultaneously evaluated with inertial sensors and the smartphone application. A total of 248 angles were compared for concurrent validity. Inter-tester and intra-tester reliability were evaluated through scoring of images with the smartphone application by two testers, and re-scoring images by the same tester.
Results: Very high correlation was observed between both methods for ROM in all neck movements and JPS in left-side lateral flexion (r>0.9), and high for JPS in the rest of movements (r>0.8). Bland-Altman plots always demonstrated absolute agreement. Inter-and intra-tester reliability was perfect for JPS and ROM in all the neck movements (ICC>0.81).
Conclusions: This smartphone-based application is valid and reliable for evaluating head repositioning and cervical ROM compared with inertial sensors in healthy and young adults. Health professionals could use it in an easier and portable way in field conditions.
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http://dx.doi.org/10.1515/bmt-2021-0229 | DOI Listing |
Women Health
January 2025
Medical College of Georgia, Augusta University, Augusta, Georgia, USA.
A novel breastfeeding mobile app was created. We aim to determine if patients who utilize the app will have longer breastfeeding duration, improved breastfeeding self-efficacy scores at 1-year follow-up, and higher exclusive breastfeeding rates at 6 months postpartum. Participants were randomized, with 45 to the intervention and 48 to the control groups.
View Article and Find Full Text PDFJMIR AI
January 2025
Human-Computer Interaction and Human-Centered AI Systems Lab, AI for Healthcare Lab, Charles V. Schaefer, Jr. School of Engineering and Science, Stevens Institute of Technology, Hoboken, NJ, United States.
Background: Acute marijuana intoxication can impair motor skills and cognitive functions such as attention and information processing. However, traditional tests, like blood, urine, and saliva, fail to accurately detect acute marijuana intoxication in real time.
Objective: This study aims to explore whether integrating smartphone-based sensors with readily accessible wearable activity trackers, like Fitbit, can enhance the detection of acute marijuana intoxication in naturalistic settings.
Clin Oral Investig
January 2025
Department of Orofacial Pain and Dysfunction, Academic Centre for Dentistry Amsterdam (ACTA), University of Amsterdam and Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
Objectives: In recent years, a smartphone-based ecological momentary assessment (EMA) approach for assessing awake bruxism (AB) has attracted growing interest, both in clinical and research settings. The present study was designed to investigate subjects' experience using an EMA-based smartphone application to detect factors that could hamper or facilitate its use for clinical and research purposes.
Materials And Methods: Thirty-two patients with temporomandibular disorders (TMDs) pain (14 males, 18 females; mean age 28.
SAGE Open Nurs
December 2024
Faculty of Nursing Science, Padjadjaran University of Padjadjaran Bandung, Indonesia.
Introduction: In all countries, the burden of mental disorders (MDs) spans the entire life course. Smartphones are currently widely used by families with a history of MD looking for the required mental health information. The use of digital media is an alternative to improving the ability of families to care for person with MD at home.
View Article and Find Full Text PDFJ Yeungnam Med Sci
December 2024
Department of Internal Medicine, Yeungnam University College of Medicine, Daegu, Korea.
The coronavirus disease 2019 pandemic has underscored the limitations of traditional diagnostic methods, particularly in ensuring the safety of healthcare workers and patients during infectious outbreaks. Smartphone-based digital stethoscopes enhanced with artificial intelligence (AI) have emerged as potential tools for addressing these challenges by enabling remote, efficient, and accessible auscultation. Despite advancements, most existing systems depend on additional hardware and external processing, increasing costs and complicating deployment.
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