Robust Continuous Hand Motion Recognition Using Wearable Array Myoelectric Sensor

Distributed recognition of human actions using wearable motion sensor networks

We propose a distributed recognition framework to classify continuous human actions using a low-bandwidth wearable motion sensor network, called distributed sparsity classifier (DSC). The algorithm classifies human actions using a set of training motion sequences as prior examples. It is also capable of rejecting outlying actions that are not in the training categories. The classification is op...

Robust continuous speech recognition using a microphone array

Gait Recognition Using Wearable Motion Recording Sensors

This paper presents an alternative approach, where gait is collected by the sensors attached to the person’s body. Such wearable sensors record motion (e.g. acceleration) of the body parts during walking. The recorded motion signals are then investigated for person recognition purposes. We analyzed acceleration signals from the foot, hip, pocket and arm. Applying various methods, the best EER o...

Activity Recognition Invariant to Sensor Orientation with Wearable Motion Sensors

Most activity recognition studies that employ wearable sensors assume that the sensors are attached at pre-determined positions and orientations that do not change over time. Since this is not the case in practice, it is of interest to develop wearable systems that operate invariantly to sensor position and orientation. We focus on invariance to sensor orientation and develop two alternative tr...

Robust continuous speech recognition system based on a microphone array

In this paper, a robust speech recognition system for videoconference applications is presented based on a microphone array. By means of a microphone array, the speech recognition system is able to know the position of the users and increase the signal-to-noise (SNR) ratio between the desired speaker signal and the interferences from the other users. The user positions are estimated by means of...