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INPHOVIS:Interactive visual analytics for smartphone-based digital phenotyping

Visual Informatics 2023年第2期7卷 13-29页

作者： Hamid Mansoor Walter Gerych Abdulaziz Alajaji Luke Buquicchio Kavin Chandrasekaran Emmanuel Agu Elke Rundensteiner angela incollingo rodriguez Worcester Polytechnic Institute USA

Digital phenotyping is the characterization of human behavior patterns based on data from digital devices such as smartphones in order to gain insights into the users’state and especially to identify *** support supervised machine learning,digital phenotyping requires gathering data from study participants’smartphones as they live their ***,participants are then asked to provide ground truth labels about their health *** such complex data is challenging due to limited contextual information and imperfect health/wellness *** propose INteractive PHOne-o-typing VISualization(INPHOVIS),an interactive visual framework for exploratory analysis of smartphone health data to study *** visualization work has focused on mobile health data with clear semantics such as steps or heart rate data collected using dedicated health devices and wearables such as ***,unlike smartphones which are owned by over 85 percent of the US population,wearable devices are less prevalent thus reducing the number of people from whom such data can be *** contrast,the‘‘low-level"sensor data(e.g.,accelerometer or GPS data)supported by INPHOVIS can be easily collected using *** visualizations are designed to provide the essential contextualization of such data and thus help analysts discover complex relationships between observed sensor values and health-predictive *** guide the design of INPHOVIS,we performed a hierarchical task analysis of phone-o-typing requirements with health domain *** then designed and implemented multiple innovative visualizations integral to INPHOVIS including stacked bar charts to show diurnal behavioral patterns,calendar views to visualize day-level data along with bar charts,and correlation views to visualize important wellness predictive *** demonstrate the usefulness of INPHOVIS with walk-throughs of use *** also evaluated INPHOVIS with expert feedb

关键词： Interactive visual analytics Smartphone-sensed data Digital phenotyping

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