{"id":3997,"date":"2022-09-15T14:26:31","date_gmt":"2022-09-15T18:26:31","guid":{"rendered":"https:\/\/www.med.unc.edu\/medicine\/geriatrics\/?page_id=3997"},"modified":"2023-04-06T15:42:45","modified_gmt":"2023-04-06T19:42:45","slug":"smart-and-connected-health","status":"publish","type":"page","link":"https:\/\/www.med.unc.edu\/medicine\/geriatrics\/research\/dr-john-batsis-research\/federally-funded-projects\/smart-and-connected-health\/","title":{"rendered":"Smart and Connected Health"},"content":{"rendered":"

Project:<\/strong> Smart and Connected Health: Interdisciplinary Collaborative Research: Exploiting Voice Interactive System for Early Detection of Cognitive Decline<\/p>\n

Grant Number:<\/strong> National Institute on Aging R01AG067416<\/p>\n

Early detection of the cognitive decline involved in Alzheimer\u2019s Disease and Related Dementias (ADRD) in older adults living alone is essential for developing, planning, and initiating interventions and support systems to improve patients\u2019 everyday function and quality of life. Conventional, clinic-based methods for early diagnosis are expensive, time-consuming, and impractical for large-scale screening.<\/p>\n

This project aims to develop a low-cost, passive, and practical home-based assessment method using Voice Assistant Systems (VAS) for early detection of cognitive decline, including a set of novel data mining techniques for sparse time-series speech. If successful, the proposed system may be widely disseminated for the early diagnosis of cognitive impairment to complement existing diagnostic modalities that could ultimately enable long-term patient and caregiver planning to maintain individual\u2019s independence at home.<\/p>\n

Key Collaborators<\/h4>\n

Xiaohui Liang (PI), David Kotz, Brian MacWhinney, Robert M. Roth<\/p>\n

Key Papers<\/h4>\n
    \n
  1. \n

    Zhu Y, Liang X, Batsis JA<\/strong>, Roth RM. Exploring Deep Transfer Learning Techniques for Alzheimer’s Dementia Detection. Front Comput Sci. 2021 May;3:624683. doi: 10.3389\/fcomp.2021.624683. Epub 2021 May 12. PMID: 34046588; PMCID: PMC8153512.<\/p>\n<\/li>\n

  2. \n

    Liang X, Batsis JA<\/strong>, Zhu Y, Driesse TM, Roth RM, Kotz D, MacWhinney B. Evaluating Voice-Assistant Commands for Dementia Detection. Comput Speech Lang. 2022 Mar;72:101297. doi: 10.1016\/j.csl.2021.101297. Epub 2021 Sep 22. PMID: 34764541; PMCID: PMC8577405.<\/p>\n<\/li>\n

  3. \n

    Zhu Y, Liang X, Batsis JA<\/strong>, Roth RM. Domain-Aware Intermediate PreTraining for Dementia Detection with Limited Data. 30 pages. Domain-aware Intermediate Pretraining for Dementia Detection with Limited Data. Conference of the International Speech Communication Association (Interspeech) 2022 [In Press]\n<\/li>\n

  4. \n

    Liang X, Batsis JA<\/strong>, Yuan J, Zhu Y, Driesse TM, Schultz J. Voice-assisted Food Recall using Voice Assistants. 16 pages [Submitted May 15th, 2022]\n<\/li>\n

  5. \n

    Zhu Y, Tran B, Liang X, Batsis JA<\/strong>, Roth RM. Towards Interpretability of Speech Pause in Dementia Detection Using Adversarial Learning. 6 pages [In Press, January 21st, 2022]\n<\/li>\n

  6. \n

    Zhu Y, Obyat A, Liang X, Batsis JA<\/strong>, Roth R. WavBERT: Exploiting Semantic and Non-semantic Speech using Wav2vec and BERT for Dementia Detection. 5 pages. Interspeech 2021 In Press, June 2nd, 2021.<\/p>\n<\/li>\n

  7. \n

    Spangler HB, Driesse TM, Lynch DH, Liang X, Roth RM, Kotz D, Fortuna K, Batsis JA<\/strong>. Privacy concerns of older adults using voice assistant systems. J Am Geriatr Soc. 2022 Aug 26. doi: 10.1111\/jgs.18009. Epub ahead of print. PMID: 36027568.<\/p>\n<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"

    Project: Smart and Connected Health: Interdisciplinary Collaborative Research: Exploiting Voice Interactive System for Early Detection of Cognitive Decline Grant Number: National Institute on Aging R01AG067416 Early detection of the cognitive decline involved in Alzheimer\u2019s Disease and Related Dementias (ADRD) in older adults living alone is essential for developing, planning, and initiating interventions and support systems … Read more<\/a><\/p>\n","protected":false},"author":106633,"featured_media":0,"parent":4027,"menu_order":2,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"layout":"","cellInformation":"","apiCallInformation":"","footnotes":"","_links_to":"","_links_to_target":""},"class_list":["post-3997","page","type-page","status-publish","hentry","odd"],"acf":[],"yoast_head":"\nSmart and Connected Health - Division of Geriatric Medicine<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.med.unc.edu\/medicine\/geriatrics\/research\/dr-john-batsis-research\/federally-funded-projects\/smart-and-connected-health\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Smart and Connected Health - 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