International Business Machines Corporation

Tian Hao

Jeffrey L Rogers

Stefan Harrer

Jianbin Tang

Hung-Yang Chang

Stefan Von Cavallar

Umar Asif

Xinxin Zhu

Erhan Bilal

Stefan Renard Maetschke

Deval Samirbhai Mehta

Kun Lin

A method, a structure, and a computer system for privacy-preserving motion analysis. Embodiments may include identifying one or more joints of a user based on collected data and generating one or more 3D representations of the one or more joints of the user. Embodiments may further include anonymizing the one or more 3D representations, classifying one or more actions of the user based on the one or more 3D representations, wherein the classifying outputs an action score, and exporting at least one of the one or more actions and the action score.

Privacy-preserving motion analysis

A method, a structure, and a computer system for privacy-preserving motion analysis. Embodiments may include collecting data corresponding to a user with one or more sensors and identifying one or more joints of the user based on the data. Embodiments may additionally include generating one or more 3D representations of the one or more joints of the user and anonymizing the one or more 3D representations by applying thereto a joint-centering and a random shuffling. Embodiments may further include classifying one or more actions of the user based on analysing the one or more 3D representations, and exporting at least one of the data and the one or more actions.

Embodiments of the present invention are directed to physiological sensing in a wearable device. Aspects include generating a multi-faceted feedback for a user. Generating the multi-faceted feedback includes generating a baseline physiological sampling schedule for a user, generating a quality-aware feedback of the user, generating a user-state-aware feedback of the user, and generating a context-aware feedback of the user. Aspects also include generating an adjusted physiological sampling schedule for the user based at least in part upon the multi-faceted feedback.

Continuous physiological sensing in energy-constrained wearables

A method, a structure, and a computer system for assessing user mobility. The exemplary embodiments may include collecting mobility data corresponding to a user and extracting one or more low level features from the mobility data. The exemplary embodiments may further include extracting one or more clinical level features from the low level features and assessing one or more health conditions of the user based on applying one or more models to the one or more clinical level features.

Mobility analysis

Embodiments of the present invention are directed to a computer-implemented method for stress monitoring. Methods include receiving, by a processor, a plurality of user stress labels corresponding to a plurality of events. Methods also include determining an individualized stress profile based at least in part upon the user stress labels. Methods also include receiving heart rate sensor data from a wearable device. Methods also include extracting a cardiovascular feature from the heart rate sensor data. Methods also include determining a stress index based at least in part upon the individualized stress profile and the cardiovascular feature. Methods also include outputting the stress index.

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White Plains, NY, United States of America

Tian Hao