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Adhyapak N, Abboud MA, Rao PS, Kar A, Mignot E, Delucca G, Smagula SF, Krishnan V. Stability and Volatility of Human Rest-Activity Rhythms: Insights from Very Long Actograms (VLAs). MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.01.22.24301243. [PMID: 38370763 PMCID: PMC10871462 DOI: 10.1101/2024.01.22.24301243] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
Importance Wrist-worn activity monitors provide biomarkers of health by non-obtrusively measuring the timing and amount of rest and physical activity (rest-activity rhythms, RARs). The morphology and robustness of RARs vary by age, gender, and sociodemographic factors, and are perturbed in various chronic illnesses. However, these are cross-sectionally derived associations from recordings lasting 4-10 days, providing little insights into how RARs vary with time. Objective To describe how RAR parameters can vary or evolve with time (~months). Design Setting and Participants 48 very long actograms ("VLAs", ≥90 days in duration) were identified from subjects enrolled in the STAGES (Stanford Technology, Analytics and Genomics in Sleep) study, a prospective cross-sectional, multi-site assessment of individuals > 13 years of age that required diagnostic polysomnography to address a sleep complaint. A single 3-year long VLA (author GD) is also described. Exposures/Intervention None planned. Main Outcomes and Measures For each VLA, we assessed the following parameters in 14-day windows: circadian/ultradian spectrum, pseudo-F statistic ("F"), cosinor amplitude, intradaily variability, interdaily stability, acrophase and estimates of "sleep" and non-wearing. Results Included STAGES subjects (n = 48, 30 female) had a median age of 51, BMI of 29.4kg/m2, Epworth Sleepiness Scale score (ESS) of 10/24 and a median recording duration of 120 days. We observed marked within-subject undulations in all six RAR parameters, with many subjects displaying ultradian rhythms of activity that waxed and waned in intensity. When appraised at the group level (nomothetic), averaged RAR parameters remained remarkably stable over a ~4 month recording period. Cohort-level deficits in average RAR robustness associated with unemployment or high BMI (>29.4) also remained stable over time. Conclusions and Relevance Through an exemplary set of months-long wrist actigraphy recordings, this study quantitatively depicts the longitudinal stability and dynamic range of human rest-activity rhythms. We propose that continuous and long-term actigraphy may have broad potential as a holistic, transdiagnostic and ecologically valid monitoring biomarker of changes in chronobiological health. Prospective recordings from willing subjects will be necessary to precisely define contexts of use.
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Affiliation(s)
- Nandani Adhyapak
- Departments of Neurology, Neuroscience and Psychiatry & Behavioral Sciences Baylor College of Medicine, Houston, TX USA
| | - Mark A. Abboud
- Departments of Neurology, Neuroscience and Psychiatry & Behavioral Sciences Baylor College of Medicine, Houston, TX USA
| | - Pallavi S.K. Rao
- Departments of Neurology, Neuroscience and Psychiatry & Behavioral Sciences Baylor College of Medicine, Houston, TX USA
| | - Ananya Kar
- Departments of Neurology, Neuroscience and Psychiatry & Behavioral Sciences Baylor College of Medicine, Houston, TX USA
| | - Emmanuel Mignot
- Stanford Center for Sleep Science and Medicine Stanford Medicine, Palo Alto CA
| | | | - Stephen F. Smagula
- Departments of Psychiatry and Epidemiology University of Pittsburgh Medical Center, Pittsburgh PA USA
| | - Vaishnav Krishnan
- Departments of Neurology, Neuroscience and Psychiatry & Behavioral Sciences Baylor College of Medicine, Houston, TX USA
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Alhazmi AK, Alanazi MA, Alshehry AH, Alshahry SM, Jaszek J, Djukic C, Brown A, Jackson K, Chodavarapu VP. Intelligent Millimeter-Wave System for Human Activity Monitoring for Telemedicine. SENSORS (BASEL, SWITZERLAND) 2024; 24:268. [PMID: 38203130 PMCID: PMC10781319 DOI: 10.3390/s24010268] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 12/13/2023] [Accepted: 12/21/2023] [Indexed: 01/12/2024]
Abstract
Telemedicine has the potential to improve access and delivery of healthcare to diverse and aging populations. Recent advances in technology allow for remote monitoring of physiological measures such as heart rate, oxygen saturation, blood glucose, and blood pressure. However, the ability to accurately detect falls and monitor physical activity remotely without invading privacy or remembering to wear a costly device remains an ongoing concern. Our proposed system utilizes a millimeter-wave (mmwave) radar sensor (IWR6843ISK-ODS) connected to an NVIDIA Jetson Nano board for continuous monitoring of human activity. We developed a PointNet neural network for real-time human activity monitoring that can provide activity data reports, tracking maps, and fall alerts. Using radar helps to safeguard patients' privacy by abstaining from recording camera images. We evaluated our system for real-time operation and achieved an inference accuracy of 99.5% when recognizing five types of activities: standing, walking, sitting, lying, and falling. Our system would facilitate the ability to detect falls and monitor physical activity in home and institutional settings to improve telemedicine by providing objective data for more timely and targeted interventions. This work demonstrates the potential of artificial intelligence algorithms and mmwave sensors for HAR.
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Affiliation(s)
- Abdullah K. Alhazmi
- Department of Electrical and Computer Engineering, University of Dayton, 300 College Park, Dayton, OH 45469, USA; (A.K.A.); (A.H.A.); (S.M.A.)
| | - Mubarak A. Alanazi
- Electrical Engineering Department, Jubail Industrial College, Royal Commission for Jubail and Yanbu, Jubail Industrial City 31961, Saudi Arabia;
| | - Awwad H. Alshehry
- Department of Electrical and Computer Engineering, University of Dayton, 300 College Park, Dayton, OH 45469, USA; (A.K.A.); (A.H.A.); (S.M.A.)
| | - Saleh M. Alshahry
- Department of Electrical and Computer Engineering, University of Dayton, 300 College Park, Dayton, OH 45469, USA; (A.K.A.); (A.H.A.); (S.M.A.)
| | - Jennifer Jaszek
- Department of Physical Therapy, University of Dayton, 300 College Park, Dayton, OH 45469, USA; (J.J.); (C.D.); (A.B.); (K.J.)
| | - Cameron Djukic
- Department of Physical Therapy, University of Dayton, 300 College Park, Dayton, OH 45469, USA; (J.J.); (C.D.); (A.B.); (K.J.)
| | - Anna Brown
- Department of Physical Therapy, University of Dayton, 300 College Park, Dayton, OH 45469, USA; (J.J.); (C.D.); (A.B.); (K.J.)
| | - Kurt Jackson
- Department of Physical Therapy, University of Dayton, 300 College Park, Dayton, OH 45469, USA; (J.J.); (C.D.); (A.B.); (K.J.)
| | - Vamsy P. Chodavarapu
- Department of Electrical and Computer Engineering, University of Dayton, 300 College Park, Dayton, OH 45469, USA; (A.K.A.); (A.H.A.); (S.M.A.)
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Sato T, Mizumoto S, Ota M, Shikano M. Implementation status and consideration for the globalisation of decentralised clinical trials: a cross-sectional analysis of clinical trial databases. BMJ Open 2023; 13:e074334. [PMID: 37821130 PMCID: PMC10582843 DOI: 10.1136/bmjopen-2023-074334] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 09/19/2023] [Indexed: 10/13/2023] Open
Abstract
OBJECTIVE To comprehensively elucidate the current landscape of decentralised clinical trials (DCTs) and identify notable aspects that can facilitate DCT implementation. DESIGN Cross-sectional analysis. SETTING Data were extracted using selected DCT-specific search terms on 4 June 2022, from the ClinicalTrials.gov database and on 2 September 2022, from the Japan Registry of Clinical Trials and Japic Clinical Trials Information. PRIMARY OUTCOME MEASURE We characterised trials based on the four components of DCT: telemedicine, home healthcare, direct-to-patient and the Internet of Healthcare Things (IoHTs)/Internet of Medical Things. RESULTS Data obtained from ClinicalTrials.gov indicated that the number of DCTs has increased annually and exponentially since 2020. DCTs for cardiovascular diseases are the most common, and the digital platform for patient monitoring is used the most in DCTs. The Japanese databases also showed that DCTs have increased in recent years, and the data on disease areas and IoHTs were similar to those obtained from the ClinicalTrials.gov database, except for the number of studies. Approximately 9.2% of DCTs were conducted across multiple regions, whereas over 80% were conducted within a single country. CONCLUSIONS This study revealed the comprehensive trend of DCTs in the USA and Japan and helped identify widely implemented DCT components and the therapeutic areas in which they are implemented. International consensus guidelines for DCTs are necessary to promote multiregional clinical trials with DCT components.
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Affiliation(s)
- Takahiro Sato
- Astellas Pharma Inc, Tokyo, Japan
- Pharmaceutical Sciences, Tokyo University of Science, Shinjuku-ku, Japan
| | - Shota Mizumoto
- Pharmaceutical Sciences, Tokyo University of Science, Shinjuku-ku, Japan
| | - Midori Ota
- Pharmaceutical Sciences, Tokyo University of Science, Shinjuku-ku, Japan
| | - Mayumi Shikano
- Pharmaceutical Sciences, Tokyo University of Science, Shinjuku-ku, Japan
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Oyama G, Burq M, Hatano T, Marks WJ, Kapur R, Fernandez J, Fujikawa K, Furusawa Y, Nakatome K, Rainaldi E, Chen C, Ho KC, Ogawa T, Kamo H, Oji Y, Takeshige-Amano H, Taniguchi D, Nakamura R, Sasaki F, Ueno S, Shiina K, Hattori A, Nishikawa N, Ishiguro M, Saiki S, Hayashi A, Motohashi M, Hattori N. Analytical and clinical validity of wearable, multi-sensor technology for assessment of motor function in patients with Parkinson's disease in Japan. Sci Rep 2023; 13:3600. [PMID: 36918552 PMCID: PMC10015076 DOI: 10.1038/s41598-023-29382-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Accepted: 02/03/2023] [Indexed: 03/16/2023] Open
Abstract
Continuous, objective monitoring of motor signs and symptoms may help improve tracking of disease progression and treatment response in Parkinson's disease (PD). This study assessed the analytical and clinical validity of multi-sensor smartwatch measurements in hospitalized and home-based settings (96 patients with PD; mean wear time 19 h/day) using a twice-daily virtual motor examination (VME) at times representing medication OFF/ON states. Digital measurement performance was better during inpatient clinical assessments for composite V-scores than single-sensor-derived features for bradykinesia (Spearman |r|= 0.63, reliability = 0.72), tremor (|r|= 0.41, reliability = 0.65), and overall motor features (|r|= 0.70, reliability = 0.67). Composite levodopa effect sizes during hospitalization were 0.51-1.44 for clinical assessments and 0.56-1.37 for VMEs. Reliability of digital measurements during home-based VMEs was 0.62-0.80 for scores derived from weekly averages and 0.24-0.66 for daily measurements. These results show that unsupervised digital measurements of motor features with wrist-worn sensors are sensitive to medication state and are reliable in naturalistic settings.Trial Registration: Japan Pharmaceutical Information Center Clinical Trials Information (JAPIC-CTI): JapicCTI-194825; Registered June 25, 2019.
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Affiliation(s)
- Genko Oyama
- Department of Neurology, Juntendo University Faculty of Medicine, 2-1-1, Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan.
| | - Maximilien Burq
- Verily Life Sciences, 269 East Grand Avenue, South San Francisco, CA, USA
| | - Taku Hatano
- Department of Neurology, Juntendo University Faculty of Medicine, 2-1-1, Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan
| | - William J Marks
- Verily Life Sciences, 269 East Grand Avenue, South San Francisco, CA, USA
| | - Ritu Kapur
- Verily Life Sciences, 269 East Grand Avenue, South San Francisco, CA, USA
| | - Jovelle Fernandez
- Takeda Pharmaceutical Company Limited, 2 Chome-1-1 Nihonbashihoncho, Chuo-Ku, Tokyo, 103-0023, Japan
| | - Keita Fujikawa
- Takeda Pharmaceutical Company Limited, 2 Chome-1-1 Nihonbashihoncho, Chuo-Ku, Tokyo, 103-0023, Japan
| | - Yoshihiko Furusawa
- Takeda Pharmaceutical Company Limited, 2 Chome-1-1 Nihonbashihoncho, Chuo-Ku, Tokyo, 103-0023, Japan
| | - Keisuke Nakatome
- Takeda Pharmaceutical Company Limited, 2 Chome-1-1 Nihonbashihoncho, Chuo-Ku, Tokyo, 103-0023, Japan
| | - Erin Rainaldi
- Verily Life Sciences, 269 East Grand Avenue, South San Francisco, CA, USA
| | - Chen Chen
- Verily Life Sciences, 269 East Grand Avenue, South San Francisco, CA, USA
| | - King Chung Ho
- Verily Life Sciences, 269 East Grand Avenue, South San Francisco, CA, USA
| | - Takashi Ogawa
- Department of Neurology, Juntendo University Faculty of Medicine, 2-1-1, Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan
| | - Hikaru Kamo
- Department of Neurology, Juntendo University Faculty of Medicine, 2-1-1, Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan
| | - Yutaka Oji
- Department of Neurology, Juntendo University Faculty of Medicine, 2-1-1, Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan
| | - Haruka Takeshige-Amano
- Department of Neurology, Juntendo University Faculty of Medicine, 2-1-1, Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan
| | - Daisuke Taniguchi
- Department of Neurology, Juntendo University Faculty of Medicine, 2-1-1, Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan
| | - Ryota Nakamura
- Department of Neurology, Juntendo University Faculty of Medicine, 2-1-1, Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan
| | - Fuyuko Sasaki
- Department of Neurology, Juntendo University Faculty of Medicine, 2-1-1, Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan
| | - Shinichi Ueno
- Department of Neurology, Juntendo University Faculty of Medicine, 2-1-1, Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan
| | - Kenta Shiina
- Department of Neurology, Juntendo University Faculty of Medicine, 2-1-1, Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan
| | - Anri Hattori
- Department of Neurology, Juntendo University Faculty of Medicine, 2-1-1, Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan
| | - Noriko Nishikawa
- Department of Neurology, Juntendo University Faculty of Medicine, 2-1-1, Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan
| | - Mayu Ishiguro
- Department of Neurology, Juntendo University Faculty of Medicine, 2-1-1, Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan
| | - Shinji Saiki
- Department of Neurology, Juntendo University Faculty of Medicine, 2-1-1, Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan
| | - Ayako Hayashi
- Takeda Pharmaceutical Company Limited, 2 Chome-1-1 Nihonbashihoncho, Chuo-Ku, Tokyo, 103-0023, Japan
| | - Masatoshi Motohashi
- Takeda Pharmaceutical Company Limited, 2 Chome-1-1 Nihonbashihoncho, Chuo-Ku, Tokyo, 103-0023, Japan
| | - Nobutaka Hattori
- Department of Neurology, Juntendo University Faculty of Medicine, 2-1-1, Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan
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Robinson T, Condell J, Ramsey E, Leavey G. Self-Management of Subclinical Common Mental Health Disorders (Anxiety, Depression and Sleep Disorders) Using Wearable Devices. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:ijerph20032636. [PMID: 36768002 PMCID: PMC9916237 DOI: 10.3390/ijerph20032636] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 01/21/2023] [Accepted: 01/28/2023] [Indexed: 05/05/2023]
Abstract
RATIONALE Common mental health disorders (CMD) (anxiety, depression, and sleep disorders) are among the leading causes of disease burden globally. The economic burden associated with such disorders is estimated at $2.4 trillion as of 2010 and is expected to reach $16 trillion by 2030. The UK has observed a 21-fold increase in the economic burden associated with CMD over the past decade. The recent COVID-19 pandemic was a catalyst for adopting technologies for mental health support and services, thereby increasing the reception of personal health data and wearables. Wearables hold considerable promise to empower users concerning the management of subclinical common mental health disorders. However, there are significant challenges to adopting wearables as a tool for the self-management of the symptoms of common mental health disorders. AIMS This review aims to evaluate the potential utility of wearables for the self-management of sub-clinical anxiety and depressive mental health disorders. Furthermore, we seek to understand the potential of wearables to reduce the burden on the healthcare system. METHODOLOGY a systematic review of research papers was conducted, focusing on wearable devices for the self-management of CMD released between 2018-2022, focusing primarily on mental health management using technology. RESULTS We screened 445 papers and analysed the reports from 12 wearable devices concerning their device type, year, biometrics used, and machine learning algorithm deployed. Electrodermal activity (EDA/GSR/SC/Skin Temperature), physical activity, and heart rate (HR) are the most common biometrics with nine, six and six reference counts, respectively. Additionally, while smartwatches have greater penetration and integration within the marketplace, fitness trackers have the most significant public value benefit of £513.9 M, likely due to greater retention.
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Affiliation(s)
- Tony Robinson
- School of Computing, Engineering, and Intelligent Systems, Ulster University, Magee Campus, Derry/Londonderry BT48 7JL, UK
- Correspondence:
| | - Joan Condell
- School of Computing, Engineering, and Intelligent Systems, Ulster University, Magee Campus, Derry/Londonderry BT48 7JL, UK
| | - Elaine Ramsey
- Department of Global Business and Enterprise, Ulster University, Magee Campus, Derry/Londonderry BT48 7JL, UK
| | - Gerard Leavey
- The Bamford Centre for Mental Health and Wellbeing, School of Psychology, Ulster University, Coleraine Campus, Cromore Rd., Coleraine BT52 1SA, UK
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Moškon M, Režen T, Juvančič M, Verovšek Š. Integrative Analysis of Rhythmicity: From Biology to Urban Environments and Sustainability. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 20:764. [PMID: 36613088 PMCID: PMC9819461 DOI: 10.3390/ijerph20010764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 12/27/2022] [Accepted: 12/27/2022] [Indexed: 06/17/2023]
Abstract
From biological to socio-technical systems, rhythmic processes are pervasive in our environment. However, methods for their comprehensive analysis are prevalent only in specific fields that limit the transfer of knowledge across scientific disciplines. This hinders interdisciplinary research and integrative analyses of rhythms across different domains and datasets. In this paper, we review recent developments in cross-disciplinary rhythmicity research, with a focus on the importance of rhythmic analyses in urban planning and biomedical research. Furthermore, we describe the current state of the art of (integrative) computational methods for the investigation of rhythmic data. Finally, we discuss the further potential and propose necessary future developments for cross-disciplinary rhythmicity analysis to foster integration of heterogeneous datasets across different domains, as well as guide data-driven decision making beyond the boundaries of traditional intradisciplinary research, especially in the context of sustainable and healthy cities.
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Affiliation(s)
- Miha Moškon
- Faculty of Computer and Information Science, University of Ljubljana, 1000 Ljubljana, Slovenia
| | - Tadeja Režen
- Centre for Functional Genomics and Bio-Chips, Institute for Biochemistry and Molecular Genetics, Faculty of Medicine, University of Ljubljana, 1000 Ljubljana, Slovenia
| | - Matevž Juvančič
- Faculty of Architecture, University of Ljubljana, 1000 Ljubljana, Slovenia
| | - Špela Verovšek
- Faculty of Architecture, University of Ljubljana, 1000 Ljubljana, Slovenia
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