Apple Inc.

Suresh B Malakar

Xiaoyuan Tu

Vinay R Majjigi

Hung A Pham

Karthik Jayaraman Raghuram

Bharath Narasimha Rao

Aditya Sarathy

Hui Lin

Embodiments are disclosed for user posture transition detection and classification using a linked biomechanical model. In an embodiment, a method comprises: obtaining motion data from a headset worn by a user; selecting features of a linked biomechanical model based on a current posture state; determining at least one probability that a posture transition occurred based on an output of a classifier, where the output of the classifier is based on the selected features and the motion data; determining a posture transition based on the at least one probability; and performing at least one action based on detection of the posture transition.

Posture transition detection and classification using linked biomechanical model

Embodiments are disclosed for indoor/outdoor detection using a mobile device, such as wearable computer (e.g., smartwatch). In an embodiment, a method comprises: receiving, by one or more processors of a wearable computer, wireless access point (AP) scan data, global navigation satellite system (GNSS) data and inertial sensor data; determining, by the one or more processors, a first state of the wearable computer based on the wireless AP scan data; determining, by the one or more processors, a second state of the wearable computer based on a comparison of the GNSS data and the inertial sensor data; and outputting, by the one or more processors, an indoor/outdoor signal indicating that the wearable computer is indoors or outdoors based on the first and second states.

Indoor/outdoor detection using a wearable computer

Growing community of inventors

Cupertino, CA, United States of America

Suresh B Malakar