S. Sivaramakrishnan

Passive Wireless MEMS Microphones for Biomedical Applications

This paper introduces passive wireless telemetry based operation for high frequency acoustic sensors. The focus is on the development, fabrication, and evaluation of wireless, battery-less SAW-IDT MEMS microphones for biomedical applications. Due to the absence of batteries, the developed sensors are small and as a result of the batch manufacturing strategy are inexpensive which enables their utilization as disposable sensors. A pulse modulated surface acoustic wave interdigital transducer (SAW-IDT) based sensing strategy has been formulated. The sensing strategy relies on detecting the ac component of the acoustic pressure signal only and does not require calibration. The proposed sensing strategy has been successfully implemented on an in-house fabricated SAW-IDT sensor and a variable capacitor which mimics the impedance change of a capacitive microphone. Wireless telemetry distances of up to 5 centimeters have been achieved. A silicon MEMS microphone which will be used with the SAW-IDT device is being microfabricated and tested. The complete passive wireless sensor package will include the MEMS microphone wire-bonded on the SAW substrate and interrogated through an on-board antenna. This work on acoustic sensors breaks new ground by introducing high frequency (i.e., audio frequencies) sensor measurement utilizing SAW-IDT sensors. The developed sensors can be used for wireless monitoring of body sounds in a number of different applications, including monitoring breathing sounds in apnea patients, monitoring chest sounds after cardiac surgery, and for feedback sensing in compression (HFCC) vests used for respiratory ventilation. Another promising application is monitoring chest sounds in neonatal care units where the miniature sensors will minimize discomfort for the newborns.

A Novel Real-Time Capacitance Estimation Methodology for Battery-Less Wireless Sensor Systems

This paper presents a novel method to read a passive capacitive sensor in telemetry by using inductive coupling. While classical inductive coupling approaches measure sensor capacitance by identifying the resonant frequency of the sensor with a sweep of radio frequency (RF) signals, the proposed method estimates the capacitance change in real-time by algebraically manipulating two measurements (the magnitude and the phase of the reflected sensor impedance). Only one RF signal is used in the proposed method instead of a frequency sweep. Analysis is provided to show that some physical parameter errors can deteriorate the capability of the proposed method in accurately measuring sensor capacitance. However, the use of a first order calibration procedure based on error analysis overcomes this shortcoming. Extensive experimental results with the proposed method combined with a first order calibration show that multifrequency and rapid changes in sensor capacitance can be estimated reliably under varying locations and orientations of the interrogator. The battery-less wireless sensors enabled by the developed technology in this paper can be widely used for measurement of fluid pressure, force, acceleration and other capacitance-change based sensor measurements.

Dynamic Model Inversion Techniques for Breath-by-Breath Measurement of Carbon Dioxide from Low Bandwidth Sensors

Respiratory CO2 measurement (capnography) is an important diagnosis tool that lacks inexpensive and wearable sensors. This paper develops techniques to enable use of inexpensive but slow CO2 sensors for breath-by-breath tracking of CO2 concentration. This is achieved by mathematically modeling the dynamic response and using model-inversion techniques to predict input CO2 concentration from the slowly varying output. Experiments are designed to identify model-dynamics and extract relevant model-parameters for a solid-state room monitoring CO2 sensor. A second-order model that accounts for flow through the sensors filter and casing is found to be accurate in describing the sensors slow response. The corresponding model-inversion algorithm is however found to be susceptible to noise sources. Techniques to remove spurious noise, while retaining quality of estimate are developed. The resulting estimate is compared with a standard-of-care respiratory CO2 analyzer and shown to effectively track variation in breath-by-breath CO2 concentration. This methodology is potentially useful for measuring fast-varying inputs to any slow sensor.

Dynamic model inversion techniques for breath-by-breath measurement of carbon dioxide from low bandwidth sensors

Respiratory CO2 measurement (capnography) is an important diagnosis tool that lacks inexpensive and wearable sensors. This paper develops techniques to enable use of inexpensive but slow CO2 sensors for breath-by-breath tracking of CO2 concentration. This is achieved by mathematically modeling the dynamic response and using model-inversion techniques to predict input CO2 concentration from the slowly varying output. Experiments are designed to identify model-dynamics and extract relevant model-parameters for a solid-state room monitoring CO2 sensor. A second-order model that accounts for flow through the sensors filter and casing is found to be accurate in describing the sensors slow response. The corresponding model-inversion algorithm is however found to be susceptible to noise sources. Techniques to remove spurious noise, while retaining quality of estimate are developed. The resulting estimate is compared with a standard-of-care respiratory CO2 analyzer and shown to effectively track variation in breath-by-breath CO2 concentration. This methodology is potentially useful for measuring fast-varying inputs to any slow sensor.

Simultaneous identification of tire cornering stiffnesses and vehicle center of gravity

INS, GPS measurements are used to simultaneously estimate the location of the center of gravity of a vehicle and the tire cornering stiffnesses. The developed method uses kinematic as well as dynamic equations of a lateral vehicle model to eliminate the bias in the yaw rate and lateral acceleration measurements. An approximation of the moment of inertia is used to combine the dynamic equations of a bicycle model and thereby estimate the tire cornering stiffnesses. The chief advantage of this method is its determinate formulation which eliminates the constraint on persistency of excitation during vehicle testing. It is shown using simulations that the accuracy of the proposed method is affected by measurement noise.

Estimators for Inductive-Coupling Based Batteryless Wireless High-Frequency Sensing

This paper develops estimation algorithms for inductively coupled batteryless wireless sensors. In such sensors, the objective is to estimate the capacitance of the embedded sensor by the measuring the influence of the sensor on an inductively coupled interrogator. The primary challenge in capacitance-estimation is the need for an accurate knowledge of the mutual inductance between the sensor and interrogator, which, varies with the location and alignment of the interrogator. Existing estimation methods that overcome this challenge are too slow for high-frequency sensing applications like microphones. This paper develops solutions designed to address the above limitation. A nonlinear adaptive observer and a cascaded filter are developed and evaluated for high-frequency capacitance estimation. Results show that the cascaded filter can accurately estimate high frequency capacitance changes with varying mutual inductance.

Development of a wireless angle sensor based on the directional radiation pattern of antennas

The directional radiation pattern of antennas is exploited to develop a high-speed wireless absolute angle measurement device. The system involves deployment of one antenna on a rotating body as the angle measurement sensor. This sensor antenna receives signals from two interrogation antennas positioned with an angular offset on a static frame of reference. The directional radiation pattern of the antennas is used to analyze the received signal strength and estimate the angle between the static and rotating frames. The signals received by the sensor antenna are analyzed using standard inexpensive hardware capable of miniaturization on a printed circuit board/chip. The key advantages of this sensor are absolute angle detection, wireless operation, high sampling rate and inexpensive fabrication. Detailed experimental results are presented that evaluate the feasibility of this new sensing concept. Experiments show that the sensor achieves better than 0.5° accuracy for static angle measurements and an accuracy of the order of 1.6° for dynamic motion measurements. An estimator that combines a gyroscope together with the developed angle sensor is then presented. The estimator is able to achieve drift-free estimates with accuracy better than 0.2° for static and 0.8° for dynamic measurements.

Evaluation of sensitivity of stiffness-sensitive electret microphones

This paper presents an evaluation of the sensitivity of a new thin-film stiffness sensing technology that utilizes commercial electret microphones. The analysis allows comparison of commercial microphones for stiffness sensing applications. A mathematical method to estimate the stiffness sensitivity of a commercial microphone from its acoustic sensitivity is developed. Experimental results are presented on the use of the developed method in a sensor that estimates carbon dioxide concentration by utilizing a carbon nanotube thin film on an electret microphone.