Christer Gerdtman

A gyro sensor based computer mouse with a USB interface : A technical aid for motor-disabled people

The aim of this study was to develop an alternative computer mouse for disabled persons. The mouse developed is a flexible input device with a multi-click function, which can be attached to a selec ...

Noise Reduction for a MEMS-Gyroscope-Based Head Mouse.

In this paper, four different signal processing algorithms which can be applied to reduce the noise from a MEMS-gyroscope-based computer head mouse are presented. MEMS-gyroscopes are small, light, cheap and widely used in many electrical products. MultiPos, a MEMS-gyroscope-based computer head mouse system was designed for persons with movement disorders. Noise such as physiological tremor and electrical noise is a common problem for the MultiPos system. In this study four different signal processing algorithms were applied and evaluated by simulation in MATLAB and implementation in a dsPIC, with aim to minimize the noise in MultiPos. The algorithms were low-pass filter, Least Mean Square (LMS) algorithm, Kalman filter and Weighted Fourier Linear Combiner (WFLC) algorithm. Comparisons and system tests show that these signal processing algorithms can be used to improve the MultiPos system. The WFLC algorithm was found the best method for noise reduction in the application of a MEMS-gyroscope-based head mouse.

A signal processing algorithm for improving the performance of a gyroscopic head-borne computer mouse

Abstract This paper presents a signal processing algorithm to remove different types of noise from a gyroscopic head-borne computer mouse. The proposed algorithm is a combination of a Kalman filter (KF), a Weighted-frequency Fourier Linear Combiner (WFLC) and a threshold with delay method (TWD). The gyroscopic head-borne mouse was developed to assist persons with movement disorders. However, since MEMS-gyroscopes are usually sensitive to environmental disturbances such as shock, vibration and temperature change, a large portion of noise is added at the same time as the head movement is sensed by the MEMS-gyroscope. The combined method is applied to the specially adapted mouse, to filter out different types of noise together with the offset and drift, with marginal need of the calculation capacity. The method is examined with both static state tests and movement operation tests. Angular position is used to evaluate the errors. The results demonstrate that the combined method improved the head motion signal substantially, with 100.0% error reduction during the static state, 98.2% position error correction in the case of movements without drift and 99.9% with drift. The proposed combination in this paper improved the static stability and position accuracy of the gyroscopic head-borne mouse system by reducing noise, offset and drift, and also has the potential to be used in other gyroscopic sensor systems to improve the accuracy of signals.

Portable sensor system for rehabilitation of patients suffering from WAD

Whiplash Associated Disorders (WAD) are several remaining symptoms after an acceleration-/deceleration injury of the neck, often due to a road accident. Common symptoms are neck pain, headache, stiffness, loss of sensation, memory impairment and concentration difficulties. The whiplash-related injuries were estimated to cost Sweden more than SEK 4 billion 2005, the main part of these costs takes the form of compensation for loss of income, as a result of incapacity for work. The aim of this project has been to develop a training and rehabilitation system for patients suffering from WAD. The portable system is based on a 2-axis gyroscopic sensor with a computer interface. The sensor system is placed on the head of the patient and movements of the head are mirrored on the computer screen. The patient is supposed to follow a visible track on the screen. This enables interactive training facilities for patients, who can use the system unsupervised in their home environment.

Perception of Delay in Computer Input Devices Establishing a Baseline for Signal Processing of Motion Sensor Systems

New computer input devices in healthcare applications using small embedded sensors need firmware filters to run smoothly and to provide a better user experience. Therefore, it has to be investigated how much delay can be tolerated for signal processing before the users perceive a delay when using a computer input device. This paper is aimed to find out a threshold of unperceived delay by performing user tests with 25 participants. A communication retarder was used to create delays from 0 to 100 ms between a receiving computer and three different USB-connected computer input devices. A wired mouse, a wifi mouse and a head-mounted mouse were used as input devices. The results of the user tests show that delays up to 50 ms could be tolerated and are not perceived as delay, or depending on the used device still perceived as acceptable.

Signal Processing Algorithms for Position Measurement with MEMS-Based Accelerometer

This paper presents signal processing algorithms for position measurements with MEMS-accelerometers in a motion analysis system. The motion analysis system is intended to analyze the human motion with MEMS-based-sensors which is a part of embedded sensor systems for health. MEMSaccelerometers can be used to measure acceleration and theoretically the velocity and position can be derived from the integration of acceleration. However, there normally is drift in the measured acceleration, which is enlarged under integration. In this paper, the signal processing algorithms are used to minimize the drift during integration by MEMS-based accelerometer. The simulation results show that the proposed algorithms improved the results a lot. The algorithm reduced the drift in one minute by about 20 meters in the simulation. It can be seen as a reference of signal processing for the motion analysis system with MEMS-based accelerometer in the future work.

A wireless low latency control system for harsh environments

The use of wireless communication technologies in the industry offer severaladvantages. One advantage is the ability to deploy sensors where they previously could noteasily be deployed, for instanc ...

Development of a Test Rig for MEMS-based Gyroscopic Motion Sensors in Human Applications

This paper describes the development of a test rig for MEMS gyroscopes. The purpose of the test rig is testing and verification of various gyroscopes that are intended for human motion analysis. The test rig will be a tool to test functionality and help in the selection process of appropriate MEMS-gyroscopes. Human movement pattern differs from mechanical motion and thus puts specific demands on the test equipment and verification procedures.

Signal Quality Improvement Algorithms for MEMS Gyroscope-Based Human Motion Analysis Systems: A Systematic Review

Motion sensors such as MEMS gyroscopes and accelerometers are characterized by a small size, light weight, high sensitivity, and low cost. They are used in an increasing number of applications. However, they are easily influenced by environmental effects such as temperature change, shock, and vibration. Thus, signal processing is essential for minimizing errors and improving signal quality and system stability. The aim of this work is to investigate and present a systematic review of different signal error reduction algorithms that are used for MEMS gyroscope-based motion analysis systems for human motion analysis or have the potential to be used in this area. A systematic search was performed with the search engines/databases of the ACM Digital Library, IEEE Xplore, PubMed, and Scopus. Sixteen papers that focus on MEMS gyroscope-related signal processing and were published in journals or conference proceedings in the past 10 years were found and fully reviewed. Seventeen algorithms were categorized into four main groups: Kalman-filter-based algorithms, adaptive-based algorithms, simple filter algorithms, and compensation-based algorithms. The algorithms were analyzed and presented along with their characteristics such as advantages, disadvantages, and time limitations. A user guide to the most suitable signal processing algorithms within this area is presented.

Embedded Sensor Systems for Health – collaboration between industry, academia and healthcare

Embedded Sensor Systems for Health (ESS-H) is a research profile at Malardalen University (MDH) in Sweden, where researchers are working together with several industrial partners, and healthcare organizations. The aim of the research profile is to develop novel embedded sensor systems promoting health. The sensor systems are developed with the aim to monitor health conditions and follow health trends of elderly at home, and also for monitoring of drivers and machine operators in order to achieve a safer work environment. Several companies are involved in the work in various ways; providing specialist competence, providing equipment and access to advanced laboratory settings, and also working as adjunct professors and providing industrial PhD students to the environment. Healthcare providers are involved in the work, providing end-user perspective to the work. This includes to provide real user-driven challenges, and involvement in all development phases.