Large-scale Sensor Dataset in a HospitalReviewed
Yasunobu Nohara, Sozo Inoue, Naoki Nakashima, Naonori Ueda, Masaru Kitsuregawa,
International Workshop on Pattern Recognition for Healthcare Analytics
In this paper, we describe a sensor dataset, which was collected in a hospital, to be used for pattern recognition and/or data mining for medical purposes. The dataset includes those of patients and nursing care in a cardiovascular center in a hospital. The experi- ment was applied for hospitalized patients who caught such as an acute cardiac infraction or angina (pre- infarction), have been applied PCI (Percutaneous Coro- nary Intervention) or CABG (Coronary Artery Bypass Graft), and have consented to the experiment. The pa- tients provided vital sensor data such as a monitor- ing cardiogram, a bed sensor to measure heart rate and breath, accelerometers, environmental sensors, and also medical information which were recorded in the electronic clinical pathways and indirectly in patients’ sensor data. At the same time, we also gathered ac- celerometer data and RFID data of real nursing in the hospital. As far as we know, these data are one of the ‘biggest data’ of sensors from a real hospital in real sit- uations.