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Fuzzy Intelligence in Monitoring Older Adults with Wearables

ABSTRACT: Monitoring older adults with wearable sensors and IoT devices requires collecting data from various sources and proliferates the number of data that should be collected in the monitoring center. Due to the large storage space and scalability, Clouds became an attractive place where the data can be stored, processed, and analyzed in order to perform the monitoring on large scale and possibly detect dangerous situations. The use of fuzzy sets in the monitoring and detection processes allows incorporating expert knowledge and medical standards while describing the meaning of various sensor readings. Calculations related to fuzzy processing and data analysis can be performed on the Edge devices which frees the Cloud platform from performing costly operations, especially for many connected IoT devices and monitored people. In this paper, we show a solution that relies on fuzzy rules while classifying health states of monitored adults and we investigate the computational cost of rules evaluation in the Cloud and on the Edge devices.

SUBMITTER: Krzhizhanovskaya V

PROVIDER: S-EPMC7302848 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Project description:This study represents the first attempt to perform a profiling analysis of the intergenerational differences in the microRNAs (miRNAs) of melanocytic neoplasms in young adult and older adult groups. Our comparative miRNA profiling provides a novel characterization of the miRnomes of melanocytic neoplasms and melanomas of different age groups and identifies a set of potential diagnostic and potential clinico-pathologic biomarkers that may serve as targets for development of novel miR-based modalities in cancer diagnosis and treatment. An exploratory miRNA analysis of 666 miRs was conducted on formalin fixed and paraffin embedded tissues from 10 adults and 10 young adults including conventional melanoma and melanocytic neoplasms of uncertain biological significance. Age-matched benign melanocytic nevi were used as controls. The comparative profiling was intentionally performed at two extremes of age, i.e., less than 30 years (Mel 30) and greater than 60 years (Mel 60). Primary melanoma in patients greater than 60 years old was characterized by the increased expression of miRs regulating TLR-MyD88-NF-kappaB pathway (hsa-miR -199a), RAS/RAB22A pathway (hsa-miR-204); growth differentiation and migration (hsa-miR337), epithelial mesenchymal transition EMT (let-7b, hsa-miR-10b/10bSTAR(*)), invasion and metastasis (hsa-miR-10b/10bSTAR(*), hsa-miR-30a/e*, hsa-miR-29c*; cellular matrix components (hsa-miR-29c*); invasion-cytokinesis (hsa-miR 99b*) compared to melanoma of younger patients. miR 211 was dramatically downregulated in primary melanoma compared to nevi controls, decreased with increasing age and was among the miRs linked to metastatic processes and potentially targeting the inflammatory receptor CCR10; Primary melanoma in young adult patients was characterized by the increased expression of hsa-miR-449a and decreased expression of hsa-miR146b, hsa-miR 214*. Among the miRs expressed at higher levels in control nevi, compared to adult or young adult melanoma, was hsa-miR 574-3p. Only 2 miRs distinguished adult from young adult-pediatric nevi, hsa-miR374a* and has-miR-566. MiR 30a* appeared to be a strong marker of differentiation in clinical stages I-II adult and pediatric melanoma, and could predict classification of melanoma tissue in the two age groups. Furthermore, lymph node status in the two age groups was characterized by the statistically significant expression of hsa-miR-30a* and hsa-miR-204 (F-test, p-value <0.001).

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Fuzzy Intelligence in Monitoring Older Adults with Wearables

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