Fall incident can cause health problem in people with special treatments and those people usually wants to live independently in their preferred environment. A fall detection method is needed to minimize the problem when human fallen and smartphone can be used as the device to detect it. Usually, people carry smartphone in any positions and can make fall detection method difficult to detect when fall occurs. The data for this study were collected by recording many sample units from each of the following human activity categories. One of the challenges of this study was the existence of human body motions whose features resembled those of body falls. In addition, unfixed smartphone positioning made human body falls harder to detect. We proposed a method based on machine learning / deep learning to accommodate detecting human activities based on data from smartphone sensors.

Fall Incident, Health, Human Body

• Dr. Maria Seraphina Astriani, S.Kom., M.T.I.