Janusz Słupik

Scalable, Wearable, Unobtrusive Sensor Network for Multimodal Human Monitoring with Distributed Control

We present the concept and implementation of unobtrusive wearable network of sensors and distributed control system for integrated monitoring - acquisition, processing, analysis of human motion and other physiological modalities. The entire system, hardware and software are scalable and compliant with the Wireless Body Area Network model. The wearable system modules can work independently and continuously indoor and outdoor. Each of the tracking and controlled subjects is wearing a Body Acquisition System (BAS). BAS is a human acquisition system for monitoring human motion and multiple physiological signals. It is built into a wearable unobtrusive smart clothing and enables to create wireless sensor network using WIFI for external communication, local hub for local data acquisition, processing and transfer. The central hub for global data processing and data exchange has been developed as Cloud Based Human Multimodal Database (CBHMD). A software application, Multimodal Data Environment (MMDE) has been built to visualize and control the acquisition and monitoring process. MMDE allows domain experts such as physicians, physiotherapists, film producers, to work with connected BASs control and react in real time. MMDE enables remote communication, data acquisition directly from BASs, diagnostics, management and maintenance of medical devices in BASs, as well as data processing using customized processes and algorithms.

The Smooth Quaternion Lifting Scheme Transform for Multi-resolution Motion Analysis

The representation and the thorough understanding of human motion is a crucial and challenging problem which has been raised in many scientific areas. This paper considers approaches in performing motion analysis with multi-resolution techniques based on rotations of joints over the time written in the form of a quaternion signal. The second generation wavelet transform constructed by the lifting scheme for the quaternion rotation representation can be used. Quaternions in terms of motion analysis are a more efficient representation of rotation than Euler angles. This paper presents the new quaternion lifting scheme building blocks for the smooth second degree transform based on the spherical cubic quaternion interpolation method (SQUAD). Also the possible applications of result multi-resolution representation as feature detection and compression are described.

Evaluation of Improvement in Orientation Estimation Through the Use of the Linear Acceleration Estimation in the Body Model

The need for broadly defined measures of human motion and estimation of motion parameters occurs in many research disciplines. The article concerns the evaluation of improvement in basic orientation estimation methods for IMU sensors, throughout the use of rigid body (segment in skeleton model) constraints. The verified method utilizes the correlation between rational motions and linear accelerations in the body model and reduces the impact of the external acceleration on the estimation of orientation. The experimental study concerns comparison of this method to other methods of leveling the influence of linear external acceleration.

Novel Lightweight Quaternion Filter for Determining Orientation Based on Indications of Gyroscope, Magnetometer and Accelerometer

The costume for acquisition of motion is example on MOCAP system based on IMU sensors using fusion of their measurements (like inertial, gyroscopic and magnetic measurements) for estimating motion parameters. In this paper a new simple and efficient fusion algorithm Lightweight Quaternion Filter is developed and implemented for estimation orientation in three dimensions. The result of estimations are compared to implemented Extended Quaternion Kalman Filter algorithm.

Implementation of Quaternion Based Lifting Scheme for Motion Data Editor Software

Motion analysis is rapidly developing area of research. Due to availability of cheaper hardware with reasonable accuracy for motion acquisition in form of various motion controllers, dedicated mainly for gaming, there are rising new research groups interested in this topic. Proposed solutions for motion analysis have a wide range of application in medicine, sport, entertainment and security. Although motion analysis is one of the most important domains of our everyday life, there are still no good tools supporting knowledge exchange and experiments in this field. In this paper we want to introduce a possibility of implementing specialised wavelet analysis in form of the lifting scheme for motion data in quaternion representation in a data flow processing framework available in Motion Data Editor (MDE) software developed at Polish-Japanese Institute of Information Technology (PJWSTK) in Bytom (Poland). We want to show how easily custom solutions can be introduced to this general purpose data processing software. Usage of this software saves time by concentrating on rapid prototyping of new algorithms and performing experiments, skipping creation of similar solutions for various data types and algorithms.

Adaptation Mechanism of Feedback in Quaternion Kalman Filtering for Orientation Estimation

In this paper an adaptation mechanism of feedback in Kalman filtering is presented for orientation estimation of rigid body. This filter fuses the measurements from Inertial Measurement Unit (IMU) sensors to determine the 3D orientation. It is well known that a factor that strongly influences the orientation measurement is the existence and magnitude of the external acceleration of the IMU sensor. To show results of simulated experiments the quaternion-based Extended Kalman Filter with and without adaptation regarding accelerometers measurement mechanism were implemented.

Wavelet features in motion data classification

The paper deals with the problem of motion data classification based on result of multiresolution analysis implemented in form of quaternion lifting scheme. Scheme processes directly on time series of rotations coded in form of unit quaternion signal. In the work new features derived from wavelet energy and entropy are proposed. To validate the approach gait database containing data of 30 different humans is used. The obtained results are satisfactory. The classification has over than 91% accuracy.