Developing Measures of Cognitive Impairment in the Real World from Consumer-Grade Multimodal Sensor Streams
| Autor: | Alessio Signorini, Han Hee Song, Hyun Joon Jung, Andrew D. Trister, Lampros Kourtis, Filip Jankovic, Roy Yaari, Luca Foschini, Melissa Pugh, Marc Sunga, Richard J. Chen, Nikki Marinsek, Belle Tseng, Jie Shen, Vera Maljkovic |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Activities of daily living
Computer science Human–computer interaction 020204 information systems 0202 electrical engineering electronic engineering information engineering Wearable computer 020201 artificial intelligence & image processing 02 engineering and technology Imputation (statistics) Cognitive impairment Missing data |
| Zdroj: | KDD |
| DOI: | 10.1145/3292500.3330690 |
| Popis: | The ubiquity and remarkable technological progress of wearable consumer devices and mobile-computing platforms (smart phone, smart watch, tablet), along with the multitude of sensor modalities available, have enabled continuous monitoring of patients and their daily activities. Such rich, longitudinal information can be mined for physiological and behavioral signatures of cognitive impairment and provide new avenues for detecting MCI in a timely and cost-effective manner. In this work, we present a platform for remote and unobtrusive monitoring of symptoms related to cognitive impairment using several consumer-grade smart devices. We demonstrate how the platform has been used to collect a total of 16TB of data during the Lilly Exploratory Digital Assessment Study, a 12-week feasibility study which monitored 31 people with cognitive impairment and 82 without cognitive impairment in free living conditions. We describe how careful data unification, time-alignment, and imputation techniques can handle missing data rates inherent in real-world settings and ultimately show utility of these disparate data in differentiating symptomatics from healthy controls based on features computed purely from device data. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|