Neurological Tremor: Sensors, Signal Processing and Emerging Applications

Neurological tremor is the most common movement disorder, affecting more than 4% of elderly people. Tremor is a non linear and non stationary phenomenon, which is increasingly recognized. The issue of selection of sensors is central in the characterization of tremor. This paper reviews the state-of-the-art instrumentation and methods of signal processing for tremor occurring in humans. We describe the advantages and disadvantages of the most commonly used sensors, as well as the emerging wearable sensors being developed to assess tremor instantaneously. We discuss the current limitations and the future applications such as the integration of tremor sensors in BCIs (brain-computer interfaces) and the need for sensor fusion approaches for wearable solutions

A Review on Key Issues and Challenges in Devices Level MEMS Testing

The present review provides information relevant to issues and challenges in MEMS testing techniques that are implemented to analyze the microelectromechanical systems (MEMS) behavior for specific application and operating conditions. MEMS devices are more complex and extremely diverse due to the immersion of multidomains. Their failure modes are distinctive under different circumstances. Therefore, testing of these systems at device level as well as at mass production level, that is, parallel testing, is becoming very challenging as compared to the IC test, because MEMS respond to electrical, physical, chemical, and optical stimuli. Currently, test systems developed for MEMS devices have to be customized due to their nondeterministic behavior and complexity. The accurate measurement of test systems for MEMS is difficult to quantify in the production phase. The complexity of the device to be tested required maturity in the test technique which increases the cost of test development; this practice is directly imposed on the device cost. This factor causes a delay in time-to-market

A Review on Key Issues and Challenges in Devices Level MEMS Testing

The present review provides information relevant to issues and challenges in MEMS testing techniques that are implemented to analyze the microelectromechanical systems (MEMS) behavior for specific application and operating conditions. MEMS devices are more complex and extremely diverse due to the immersion of multidomains. Their failure modes are distinctive under different circumstances. Therefore, testing of these systems at device level as well as at mass production level, that is, parallel testing, is becoming very challenging as compared to the IC test, because MEMS respond to electrical, physical, chemical, and optical stimuli. Currently, test systems developed for MEMS devices have to be customized due to their nondeterministic behavior and complexity. The accurate measurement of test systems for MEMS is difficult to quantify in the production phase. The complexity of the device to be tested required maturity in the test technique which increases the cost of test development; this practice is directly imposed on the device cost. This factor causes a delay in time-to-market

An aircraft and provide information about flight performance and local microclimate

Includes abstract.Includes bibliographical referencesThe application of using Unmanned Aerial Vehicles (UAVs) to locate thermal updraft currentsis a relatively new topic. It was first proposed in 1998 by John Wharington, and, subsequently, several researchers have developed algorithms to search and exploit thermals. However, few people have physically implemented a system and performed field testing. The aim of this project was to develop a low cost system to be carried on a glider to detect thermals effectively. A system was developed from the ground up and consisted of custom hardware and software that was developed specifically for aircraft. Data fusion was performed to estimate the attitude of the aircraft; this was done using a direction cosine (DCM) based method. Altitude and airspeed data were fused by estimating potential and kinetic energy respectively; thus determining the aircraft’s total energy. This data was then interpreted to locate thermal activity. The system comprised an Inertial Measurement Unit (IMU), airspeed sensor, barometric altitude sensor, Global Positioning System (GPS), temperature sensor, SD card and a realtime telemetry link. These features allowed the system to determine aircraft position, height, airspeed and air temperature in realtime. A custom-designed radio controlled (RC) glider was constructed from composite materials in addition to a second 3.6 m production glider that was used during flight testing. Sensor calibration was done using a wind tunnel with custom designed apparatus that allowed a complete wing with its pitot tube to be tested in one operation. Flight testing was conducted in the field at several different locations over the course of six months. A total of 25 recorded flights were made during this period. Both thermal soaring and ridge soaring were performed to test the system under varying weather conditions. A telemetry link was developed to transfer data in realtime from the aircraft to a custom ground station. The recorded results were post-processed using Matlab and showed that the system was able to detect thermal updrafts. The sensors used in the system were shown to provide acceptable performance once some calibration had been performed. Sensor noise proved to be problematic, and time was spent alleviating its effects

Fusion of sensor information to measure the total energy of an aircraft and provide information about flight performance and local microclimate

The application of using Unmanned Aerial Vehicles (UAVs) to locate thermal updraft currents is a relatively new topic. It was first proposed in 1998 by John Wharington, and, subsequently, several researchers have developed algorithms to search and exploit thermals. However, few people have physically implemented a system and performed field testing. The aim of this project was to develop a low cost system to be carried on a glider to detect thermals effectively. A system was developed from the ground up and consisted of custom hardware and software that was developed specifically for aircraft. Data fusion was performed to estimate the attitude of the aircraft; this was done using a direction cosine (DCM) based method. Altitude and airspeed data were fused by estimating potential and kinetic energy respectively; thus determining the aircraft's total energy. This data was then interpreted to locate thermal activity. The system comprised an Inertial Measurement Unit (IMU), airspeed sensor, barometric altitude sensor, Global Positioning System (GPS), temperature sensor, SD card and a realtime telemetry link. These features allowed the system to determine aircraft position, height, airspeed and air temperature in realtime. A custom-designed radio controlled (RC) glider was constructed from composite materials in addition to a second 3.6 m production glider that was used during flight testing. Sensor calibration was done using a wind tunnel with custom designed apparatus that allowed a complete wing with its pitot tube to be tested in one operation. Flight testing was conducted in the field at several different locations over the course of six months. A total of 25 recorded flights were made during this period. Both thermal soaring and ridge soaring were performed to test the system under varying weather conditions. A telemetry link was developed to transfer data in realtime from the aircraft to a custom ground station. The recorded results were post-processed using Matlab and showed that the system was able to detect thermal updrafts. The sensors used in the system were shown to provide acceptable performance once some calibration had been performed. Sensor noise proved to be problematic, and time was spent alleviating its effects. Results showed that the system was able to measure airspeed to within ± 1 km/h. The standard deviation of the altitude estimate was determined to be 0.94 m. This was deemed to be satisfactory. The system was highly reliable and no faults occurred during operation. In conclusion, the project showed that inexpensive sensors and low power microcontrollers could be used very effectively for the application of detecting thermals

Material Fatigue And Reliability Of Mems Accelerometers

MEMS (Microelectromechanical System) reliability has been a very important issue, especially for safety critical applications. Due to the diversity and multiple energy domains involved, MEMS devices are vulnerable to various failure mechanisms. MEMS reliability under different failure mechanisms should be analyzed separately. Since most of MEMS devices contain movable parts, material fatigue and aging under long-term repeated cycling load may lead to potential device failure, which in turn degrades the device reliability. In this paper, the reliability of poly-silicon MEMS comb accelerometers under material fatigue failure mechanism is analyzed. Based on ANSYS stress simulation, the mean-time-to-failure (MTTF) lifetimes and failure rates for both BISR (built-in self-repairable) and non-BISR poly-silicon MEMS comb accelerometers are derived. Simulation results show that the fatigue lifetime of MEMS accelerometers made by poly-silicon material can be good enough for general purpose applications. However, for some 'weak' devices with certain structure defects, the material fatigue and aging may become potential threats. Compared to non-BISR design, BISR MEMS accelerometer demonstrates effective reliability improvement due to redundancy repair. MEMS reliability under material fatigue for other MEMS materials will be further studied in the future.http://ieeexplore.ieee.org.libproxy.bridgeport.edu/stamp/stamp.jsp?tp=&arnumber=4641187&tag=