Mobile Activity Recognition and Bigdata in Medical and Caregiving Domains

Sozo Inoue,
Robotics and Computer Science: Toward Continued Collaboration between CCNY and Kyutech
(Not Available)
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In this talk, we introduce activity recognition technology using
mobile type sensors including smartphones and applications to medical
and nursing fields. Although a lot of activity recognition technology
has already been introduced, there are many challenges in collecting
realistic datasets and developing algorithms for complicated and
long-term activities. To this problem, from our research, we proposed
a method [UbiComp2015] that uses prior knowledge of the activity
segment of the day, and a method that automatically corrects when the
timing of the labels are inaccurate [MobiQuitou2016]. We also proposed
a method [MobiQuitous2016] that corrects differences among individuals
by transfer learning. Along with these works, we talk about the future
prediction of nursing work volume and patient prognosis in combination
with medical data in the hospital[UBI16], and talk about the trial of
recognizing whole staffs' activities in nursing homes for 4 months

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