System-Identification-Based Activity Recognition Algorithms With Inertial Sensors.

This paper focuses on activity recognition using a single wearable inertial measurement sensor placed on the subject's chest. The ten activities that need to be identified include lying down, standing, sitting, bending and walking, among others. The activity recognition approach is based on using and identifying a transfer function associated with each activity.

Real world validation of activity recognition algorithm and development of novel behavioral biomarkers of falls in aged control and movement disorder patients.

The use of wearable sensors in movement disorder patients such as Parkinson's disease (PD) and normal pressure hydrocephalus (NPH) is becoming more widespread, but most studies are limited to characterizing general aspects of mobility using smartphones. There is a need to accurately identify specific activities at home in order to properly evaluate gait and balance at home, where most falls occur. We developed an activity recognition algorithm to classify multiple daily living activities including high fall risk activities such as sit to stand transfers, turns and near-falls using data from 5 inertial sensors placed on the chest, upper-legs and lower-legs of the subjects.

Toward Completely Sampled Extracellular Neural Recording During fMRI.

This work aims to estimate severe fMRI scanning artifacts in extracellular neural recordings made at ultrahigh magnetic field strengths in order to remove the artifact interferences and uncover the complete neural electrophysiology signal. We build on previous work that used PCA to denoise EEG recorded during fMRI, adapting it to cover the much larger frequency range (1-6000 Hz) of the extracellular field potentials (EFPs) observed by extracellular neural recordings. We examine the singular value decomposition (SVD)-PCA singular value shrinkage (SVS) and compare two shrinkage rules and a sliding template subtraction approach.

Reference-Free Adaptive Filtering of Extracellular Neural Signals Recording in Ultra-High Field Magnetic Resonance Imaging Scanners: Removal of Periodic Interferences.

This paper focuses on the removal of periodic artifacts from neural signals recorded in rats in ultra-high field (UHF) MRI scanners, using a reference free adaptive feedforward method. Recording extracellular neural signals in the UHF environment is motivated by the desire to combine neural recording and UHF functional magnetic resonance imaging (fMRI) to better understand brain function. However, the neural signals are found to have extremely high noise artifacts of a periodic nature due to electromagnetic interference and due to small oscillatory motions.

Novel Composite Gold-Aluminum Electrode with Application to Neural Recording and Stimulation in Ultrahigh Field Magnetic Resonance Imaging Scanners.

Traditional electrodes used for neural recording and stimulation generate large regions of signal void (no functional MRI signal) when used in ultrahigh field (UHF) MRI scanners. This is a significant disadvantage when simultaneous neural recording/stimulation and fMRI signal acquisition is desired, for example in understanding the functional mechanisms of deep brain stimulation (DBS). In this work, a novel gold-aluminum microwire neural electrode is presented which overcomes this disadvantage.

Adaptive virtual referencing for the extraction of extracellularly recorded action potentials in noisy environments.

Objective: Removal of common mode noise and artifacts from extracellularly measured action potentials, herein referred to as spikes, recorded with multi-electrode arrays (MEAs) which included severe noise and artifacts generated by an ultrahigh field (UHF) 16.4 Tesla magnetic resonance imaging (MRI) scanner.

Approach: An adaptive virtual referencing (AVR) algorithm is used to remove artifacts and thus enable extraction of neural spike signals from extracellular recordings in anesthetized rat brains.

Vibrotactile perception in Dupuytren disease.

Purpose: Dupuytren disease (DD) has been associated with enlarged Pacinian corpuscles (PCs) and with PCs having a greater number of lamellae. Based on these associations, we hypothesized that subjects with DD would have altered sensitivity to high-frequency vibrations and that the changes would be more prominent at 250 Hz, where healthy subjects demonstrate the highest sensitivity.

Methods: A novel device was created to deliver vibrations of specific frequencies and amplitudes to the fingers and palm.

Observer-Based Deconvolution of Deterministic Input in Coprime Multichannel Systems With Its Application to Noninvasive Central Blood Pressure Monitoring.

Estimating central aortic blood pressure (BP) is important for cardiovascular (CV) health and risk prediction purposes. CV system is a multichannel dynamical system that yields multiple BPs at various body sites in response to central aortic BP. This paper concerns the development and analysis of an observer-based approach to deconvolution of unknown input in a class of coprime multichannel systems applicable to noninvasive estimation of central aortic BP.

An Instrumented Urethral Catheter with a Distributed Array of Iontronic Force Sensors.

This paper develops a novel instrumented urethral catheter with an array of force sensors for measuring the distributed pressure in a human urethra. The catheter and integrated portions of the force sensors are fabricated by the use of 3D printing using a combination of both soft and hard polymer substrates. Other portions of the force sensors consisting of electrodes and electrolytes are fabricated separately and assembled on top of the 3D-printed catheter to create a soft flexible device.

Computation of Magnetic Field Distortions and Impact on T*-weighted MRI with Application to Magnetic Susceptibility Parameter Estimation.

A two-step numerical computation of T* signal weighting maps in gradient echo magnetic resonance imaging in the presence of an object with varied susceptibility property is presented. In the first step, the magnetic scalar potential is computed for an arbitrary 2D magnetic susceptibility distribution using an algebraic solver. The corresponding magnetic field disturbance is computed from the magnetic scalar potential.

Paper-Based Supercapacitive Mechanical Sensors.

Paper has been pursued as an interesting substrate material for sensors in applications such as microfluidics, bio-sensing of analytes and printed microelectronics. It offers advantages of being inexpensive, lightweight, environmentally friendly and easy to use. However, currently available paper-based mechanical sensors suffer from inadequate range and accuracy.

Wearable Water Content Sensor Based on Ultrasound and Magnetic Sensing.

Fluid accumulation in the lower extremities is an early indicator of disease deterioration in cardiac failure, chronic venous insufficiency and lymphedema. At-home wearable monitoring and early detection of fluid accumulation can potentially lead to prompt medical intervention and avoidance of hospitalization. Current methods of fluid accumulation monitoring either suffer from lack of specificity and sensitivity or are invasive and cost-prohibitive to use on a daily basis.

Novel Supercapacitor-Based Force Sensor Insensitive to Parasitic Noise.

Traditional capacitive sensors suffer from significant parasitic noise when used in liquid environments or inside the human body. The parasitic noise overwhelms the force response of the sensor and makes it impossible to calculate the absolute force experienced by the sensor. This article focuses on the development of a supercapacitor based force sensor that is immune to parasitic noise.

Transparent Flexible Active Faraday Cage Enables In Vivo Capacitance Measurement in Assembled Microsensor.

Capacitive micro-sensors such as accelerometers, gyroscopes and pressure sensors are increasingly used in the modern electronic world. However, the in vivo use of capacitive sensing for measurement of pressure or other variables inside a human body suffers from significant errors due to stray capacitance. This paper proposes a solution consisting of a transparent thin flexible Faraday cage that surrounds the sensor.

Instrumented Urethral Catheter and Its Ex Vivo Validation in a Sheep Urethra.

This paper designs and fabricates an instrumented catheter for instantaneous measurement of distributed urethral pressure profiles. Since the catheter enables a new type of urological measurement, a process for accurate ex-vivo validation of the catheter is developed. A flexible sensor strip is first fabricated with nine pressure sensors and integrated electronic pads for an associated sensor IC chip.

Carbon Nano-Structured Neural Probes Show Promise for Magnetic Resonance Imaging Applications.

Objective: Previous animal studies have demonstrated that carbon nanotube (CNT) electrodes provide several advantages of preferential cell growth and better signal-to-noise ratio when interfacing with brain neural tissue. This work explores another advantage of CNT electrodes, namely their MRI compatibility. MRI-compatible neural electrodes that do not produce image artifacts will allow simultaneous co-located functional MRI and neural signal recordings, which will help improve our understanding of the brain.

Note: Development of leg size sensors for fluid accumulation monitoring.

A number of diseases can lead to fluid accumulation and swelling in the lower leg. Early detection of leg swelling can be used to effectively predict potential health risks and allows for early intervention from medical providers. Hence this note develops a novel leg size sensor based on the use of magnetic field measurement.

Flexible Distributed Pressure Sensing Strip for a Urethral Catheter.

A multi-sensor flexible strip is developed for a urethral catheter to measure distributed pressure in a human urethra. The developed sensor strip has important clinical applications in urodynamic testing for analyzing the causes of urinary incontinence in patients. There are two major challenges in the development of the sensor.

Distributed pressure sensors for a urethral catheter.

A flexible strip that incorporates multiple pressure sensors and is capable of being fixed to a urethral catheter is developed. The urethral catheter thus instrumented will be useful for measurement of pressure in a human urethra during urodynamic testing in a clinic. This would help diagnose the causes of urinary incontinence in patients.

Sensors on instrumented socks for detection of lower leg edema--An in vitro study.

This paper presents the design, sensing principles and in vitro evaluation of a novel instrumented sock intended for prediction and prevention of acute decompensated heart failure. The sock contains a drift-free ankle size sensor and a leg tissue elasticity sensor. Both sensors are inexpensive and developed using innovative new sensing ideas.

Magnetic sensor for configurable measurement of tension or elasticity with validation in animal soft tissues.

This paper presents a novel Hall-effect-based magnetic sensor for handheld measurement of either elasticity or tension in soft tissues. A theoretical model is developed for the mechanical interaction of the sensor with the tissue, and conditions are established under which the separate effects of tension or elasticity can be measured. A model of the magnetic field within the sensor is developed and a technique to estimate the sensor response in the presence of multiple magnets is established.

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

Respiratory CO(2) measurement (capnography) is an important diagnosis tool that lacks inexpensive and wearable sensors. This paper develops techniques to enable use of inexpensive but slow CO(2) sensors for breath-by-breath tracking of CO(2) concentration. This is achieved by mathematically modeling the dynamic response and using model-inversion techniques to predict input CO(2) concentration from the slow-varying output.

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.