عنوان انگلیسی مقاله:
Age estimation from the biometric information of hand bones_ Development of new formulas
ترجمه فارسی عنوان مقاله:
برآورد سن از اطلاعات بیومتریک استخوان های دست: توسعه فرمول های جدید
Sciencedirect - Elsevier - Forensic Science International, 322 (2021) 110777: doi:10:1016/j:forsciint:2021:110777
Biometric monitoring technologies (BioMeTs) have attracted the attention of the health care community because
of their user-friendly form factor and multi-sensor data-collection capabilities. The potential benefits of remote
monitoring for collecting comprehensive, longitudinal, and contextual datasets span therapeutic areas, and both
chronic and acute disease settings. Importantly, multimodal BioMeTs unlock the ability to generate rich
contextual data to augment digital measures. Currently, the availability of devices is no longer the main factor
limiting adoption but rather the ability to integrate fit-for-purpose BioMeTs reliably and safely into clinical care.
We provide a critical review of the state of art for multimodal BioMeTs in clinical care and identify three unmet clinical needs: 1) expand the abilities of existing ambulatory unimodal BioMeTs; 2) adapt standardized clinical test protocols ("spot checks’’) for use under free living conditions; and 3) develop novel applications to manage rehabilitation and chronic diseases. As the field is still in an early and quickly evolving state, we make practical recommendations: 1) to select appropriate BioMeTs; 2) to develop composite digital measures; and 3) to design interoperable software to ingest, process, delegate, and visualize the data when deploying novel clinical applications. Multimodal BioMeTs will drive the evolution from in-clinic assessments to at-home data collection with a focus on prevention, personalization, and long-term outcomes by empowering health care providers with knowledge, delivering convenience, and an improved standard of care to patients.
Keywords: Digital medicine | Wearables | Multimodal assessment | Digital measures