Background: A digital medicine system (DMS) has been developed to measure and report adherence to an atypical antipsychotic, aripiprazole, in psychiatric patients. The DMS consists of 3 components: ingestible sensor embedded in a medication tablet, wearable sensor, and secure mobile and cloud-based applications. An umbrella study protocol was designed to rapidly assess the technical performance and safety of the DMS in multiple substudies to guide the technology development.
Methods: Two sequential substudies enrolled 30 and 29 healthy volunteers between March-April 2014 and February-March 2015, respectively, to assess detection accuracy of the ingestible sensor by the DMS and the latency period between ingestion and detection of the ingestion by the wearable sensor or the cloud-based server.
Results: The first substudy identified areas for improvement using early versions of the wearable sensor and the mobile application. The second substudy tested updated versions of the components and showed an overall ingestion detection rate of 96.6%. Mean latency times for the signal transmission were 1.1-1.3 minutes (from ingestion to the wearable sensor detection) and 6.2-10.3 minutes (from the wearable sensor detection to the server detection). Half of transmissions were completed in < 2 minutes, and ~90% of ingestions were registered by the smartphone within 30 minutes of ingestion. No serious adverse events, discontinuations, or clinically significant laboratory/vital signs findings were reported.
Conclusions: The DMS implementing modified versions of the smartphone application and the wearable sensor has the technical capability to detect and report tablet ingestion with high accuracy and acceptable latency time.
Trial Registration: ClinicalTrials.gov identifier: NCT02091882.
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http://dx.doi.org/10.4088/JCP.16m10643 | DOI Listing |
Adv Sci (Weinh)
December 2024
IFIMUP Physics for Advanced Materials, Nanotechnology and Photonics, Department of Physics and Astronomy, Faculty of Sciences, University of Porto, Rua do Campo Alegre, Porto, 4169-007, Portugal.
In recent advancements within sensing technology, driven by the Internet of Things (IoT), significant impacts are observed on health sector applications, notably through wearable electronics like electronic tattoos (e-tattoos). These e-tattoos, designed for direct contact with the skin, facilitate precise monitoring of vital physiological parameters, including body heat, a critical indicator for conditions such as inflammation and infection. Monitoring these indicators can be crucial for early detection of chronic conditions, steering toward proactive healthcare management.
View Article and Find Full Text PDFObjective: To identify lifting actions and count the number of lifts performed in videos based on robust class prediction and a streamlined process for reliable real-time monitoring of lifting tasks.
Background: Traditional methods for recognizing lifting actions often rely on deep learning classifiers applied to human motion data collected from wearable sensors. Despite their high performance, these methods can be difficult to implement on systems with limited hardware resources.
ACS Appl Mater Interfaces
December 2024
School of Mechanical Engineering, Hangzhou Dianzi University, Hangzhou 310018, China.
Flexible sensors are increasingly significant in applications such as smart wearables and human-computer interactions. However, typical flexible sensors are spatially limited and can generally detect only one deformation mode. This study presents a novel multimodal flexible sensor that combines three sensing units: optoelectronics, ionic liquids, and conductive fabrics.
View Article and Find Full Text PDFFood Chem
December 2024
College of Chemistry and Chemical Engineering, Engineering Research Center of Dairy Quality and Safety Control Technology, Ministry of Education, Inner Mongolia University, 235 University West Street, Hohhot, China. Electronic address:
Monitoring of biomolecules in food plays a crucial role in safeguarding human health. Prevalent biomolecule monitoring systems are constructed predominantly from rigid materials and have inherent limitations in detection capabilities. Wearable sensors have increasingly captured attention, significantly propelling the evolution of biomolecular detection process.
View Article and Find Full Text PDFiScience
December 2024
Department of Materials Science, Faculty of Science, Srinakharinwirot University, Sukhumvit 23, Watthana, Bangkok 10110, Thailand.
Parkinson's disease (PD) prevalence is projected to reach 12 million by 2040. Wearable sensors offer a promising approach for comfortable, continuous tremor monitoring to optimize treatment strategies. Here, we present a wristwatch-like triboelectric sensor (WW-TES) inspired by automatic watches for unobtrusive PD tremor assessment.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!