BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Penn Engineering Events - ECPv6.15.18//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:Penn Engineering Events
X-ORIGINAL-URL:https://seasevents.nmsdev7.com
X-WR-CALDESC:Events for Penn Engineering Events
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/New_York
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20210314T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20211107T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20220313T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20221106T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20230312T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20231105T060000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220215T110000
DTEND;TZID=America/New_York:20220215T120000
DTSTAMP:20260406T052244
CREATED:20220208T153914Z
LAST-MODIFIED:20220208T153914Z
UID:6299-1644922800-1644926400@seasevents.nmsdev7.com
SUMMARY:ESE Spring Colloquium - "Autonomous Microsystems Based on Heterogeneously Integrated CMOS for Biological Big Data"
DESCRIPTION:Minimally invasive and chronic physiological monitoring can provide an effective means of disease prevention and early detection while the cumulative big data can unveil hidden patterns in our physiology. Yet\, current physiological monitoring tools are often bulky\, invasive\, and expensive\, limiting their sensitivity and applicability. In this talk\, I will discuss autonomous microsystems based on heterogeneously integrated CMOS\, a platform on which ideal physiological sensors and actuators can be built. \nA micro-scale optoelectronically transduced electrode (MOTE)\, an exemplary microsystem I have designed and built for tetherless neural recording\, is powered and communicates optically through a vertically integrated AlGaAs micro-scale light emitting diode (µLED)\, eliminating the needs for a battery or a RF coil; the MOTE is smaller than a human hair (~60 µm × 30 µm × 330 µm) and weighs about one 1 µg (cf. a grain of sand is about 670 µg). I will review the unique challenges and considerations in developing such heterogeneous systems in terms of device fabrication\, circuit design\, integration\, and handling/manipulation. \nWhile the MOTE is designed for neural recording\, its design methodologies can also be used to monitor other physiological parameters such as temperature\, pH\, glucose-level\, etc. I will introduce future autonomous microsystems with expanded modalities and how to interface them with existing wearables. As such microsystems become more accessible\, the resulting biological big data will help enable personalized healthcare and produce a physiological ‘digital twin’ (like the architectural digital twins of select cities) that can add a new dimension to epidemiological and aging studies.
URL:https://seasevents.nmsdev7.com/event/ese-spring-colloquium-autonomous-microsystems-based-on-heterogeneously-integrated-cmos-for-biological-big-data/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar,Colloquium
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
END:VEVENT
END:VCALENDAR