Pervasive Informatics and Persistent Actimetric Information in Health Smart Homes: From Language Model to Location Model

Abstract

To cite this version:Yannick Fouquet, Jacques Demongeot, Nicolas Vuillerme. Pervasive informatics and persistent acti- Abstract-This paper presents an approach of location model deriving from language models existing in speech recognition research. The purpose is to applicate existing model in speech recognition to predict location of an elderly person. Using statistics, the model offers up to 98.03% of good prediction location, considering only the last second of location but distinguishing days of week. Simpler than Polya's urns derived approach, this approach seems to be a good way of location modelling.

Evaluating the cost-effectiveness of an early detection of Parkinson's disease through innovative technology

“…While there is a wide range of systems available for telehealth diagnosis (Fouquet, Franco, Vuillerme, & Demongeot, 2012; Gay & Leijdekkers, 2007; Lymberis, 2003; Suzuki, Tanaka, Minami, Yamada, & Miyata, 2013), several commonalities exist. A telehealth diagnosis system must be able to i) sense characteristics pertaining to a patient’s health, ii) communicate data to a processing entity, iii) discover knowledge based on the patient’s data, and iv) provide feedback to the patient and the healthcare provider.…”

Telemonitoring of the Elderly at Home: Real-Time Pervasive Follow-up of Daily Routine, Automatic Detection of Outliers and Drifts

“…In the speech recognition domain, this problem is encountered for word prediction. Statistical approaches based on n-grams theory are often used to overcome these kinds of difficulty (Shannon 1948, Rosenfeld 1996, Fouquet 2004). The following experiment aims at applying the n-grams theory to location modelling problem.…”