{"593938":{"#nid":"593938","#data":{"type":"event","title":"PhD Defense by Erik Reinertsen","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EErik Reinertsen\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EPhD Defense\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EDate: \u003C\/strong\u003ETuesday, Aug 15, 2017\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETime: \u003C\/strong\u003E10 - 11 am\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ELocation:\u0026nbsp;\u003C\/strong\u003E\u200bEmory University School of Medicine room 170A\u003Cstrong\u003E\u200b\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ECommittee members:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u200b- Gari Clifford, DPhil (advisor)\u003Cbr \/\u003E\r\n\u200b- \u200bShamim Nemati, PhD\u003Cbr \/\u003E\r\n\u200b- \u200bAmit Shah, MD, MSCR\u003Cbr \/\u003E\r\n\u200b- \u200bEberhard Voit, PhD\u003Cbr \/\u003E\r\n\u200b- \u200bLee Cooper, PhD\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003E\u200bTitle:\u0026nbsp;\u003C\/strong\u003EDichotomizing illness from cardiovascular and activity time series\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u200b\u200b\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003E\u200b \u200b\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDigital sensors on smartphones and wearables measure huge quantities of time series data. Patterns in these da\u200bta - such as heart rate (HR) and locomotor activity -\u200b reflect changes in physiology and behavior\u200b associated with mental and\/or cardiovascular illness\u200b. However, most feature extraction approaches do not capture how \u200bnoise and \u200binformation varies with time scale, or is transferred between different signals\u200b. This thesis explores the use of\u0026nbsp;time domain, frequency domain, and complexity measures over several time scales to train machine learning algorithms to classify illness. First, a novel segmentation \u200bmethod based on periods of minimum heart rate is shown to improve the classification of post-traumatic stress disorder (PTSD) from healthy controls using heart rate variability metrics. Second, the relationship between analysis window length and classifier accuracy is evaluated in the context of using HR and activity features to dichotomize subjects with schizophrenia from healthy controls. Third, multiscale transfer entropy and network theoretical metrics of heart rate and activity are evaluated as complexity measures that contribute to the classification of atrial fibrillation and PSTD. This work \u200bcontributes to the growing field of \u200bobjective physiological \u200bsensing that \u200bcould enable long-term ambulatory monitoring of clinically significant conditions.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E-----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003ETo join the meeting on a computer or mobile phone : \u003Ca href=\u0022https:\/\/bluejeans.com\/383674918\/404385?src=calendarLink\u0022 target=\u0022_blank\u0022\u003Ehttps:\/\/bluejeans.com\/383674918\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EHere are the details for the meeting you scheduled:\u003C\/p\u003E\r\n\r\n\u003Cp\u003E-----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003EConnecting directly from a room system?\u003C\/p\u003E\r\n\r\n\u003Cp\u003E1) Dial: 199.48.152.152 or \u003Ca href=\u0022http:\/\/bjn.vc\/\u0022 target=\u0022_blank\u0022\u003Ebjn.vc\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E2) Enter Meeting ID: 383674918\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EJust want to dial in on your phone?\u003C\/p\u003E\r\n\r\n\u003Cp\u003E1) \u003Ca href=\u0022tel:(408)%20740-7256\u0022 target=\u0022_blank\u0022\u003E+1.408.740.7256\u003C\/a\u003E (United States)\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u003Ca href=\u0022tel:(888)%20240-2560\u0022 target=\u0022_blank\u0022\u003E+1.888.240.2560\u003C\/a\u003E (US Toll Free)\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u003Ca href=\u0022tel:(408)%20317-9253\u0022 target=\u0022_blank\u0022\u003E+1.408.317.9253\u003C\/a\u003E (Alternate number)\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;(\u003Ca href=\u0022http:\/\/bluejeans.com\/numbers\u0022 target=\u0022_blank\u0022\u003Ehttp:\/\/bluejeans.com\/numbers\u003C\/a\u003E)\u003C\/p\u003E\r\n\r\n\u003Cp\u003E2) Enter Meeting ID: 383674918\u003C\/p\u003E\r\n\r\n\u003Cp\u003E3) Press #\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Dichotomizing illness from cardiovascular and activity time series"}],"uid":"27707","created_gmt":"2017-08-01 19:47:07","changed_gmt":"2017-08-02 19:13:27","author":"Tatianna Richardson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2017-08-15T11:00:00-04:00","event_time_end":"2017-08-15T12:00:00-04:00","event_time_end_last":"2017-08-15T12:00:00-04:00","gmt_time_start":"2017-08-15 15:00:00","gmt_time_end":"2017-08-15 16:00:00","gmt_time_end_last":"2017-08-15 16:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"221981","name":"Graduate Studies"}],"categories":[],"keywords":[{"id":"100811","name":"Phd Defense"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1788","name":"Other\/Miscellaneous"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}