Development and Characterization of Novel Conductive Sensing Fibers for In Vivo Nerve Stimulation.

Advancements in electrode technologies to both stimulate and record the central nervous system's electrical activities are enabling significant improvements in both the understanding and treatment of different neurological diseases. However, the current neural recording and stimulating electrodes are metallic, requiring invasive and damaging methods to interface with neural tissue. These electrodes may also degrade, resulting in additional invasive procedures.

A Deep Learning Model for Automated Classification of Intraoperative Continuous EMG.

Objective: Intraoperative neurophysiological monitoring (IONM) is the use of electrophysiological methods during certain high-risk surgeries to assess the functional integrity of nerves in real time and alert the surgeon to prevent damage. However, the efficiency of IONM in current practice is limited by latency of verbal communications, inter-rater variability, and the subjective manner in which electrophysiological signals are described.

Methods: In an attempt to address these shortcomings, we investigate automated classification of free-running electromyogram (EMG) waveforms during IONM.

Cuff-Free Blood Pressure Estimation Using Pulse Transit Time and Heart Rate.

It has been reported that the pulse transit time (PTT), the interval between the peak of the R-wave in electrocardiogram (ECG) and the fingertip photoplethysmogram (PPG), is related to arterial stiffness, and can be used to estimate the systolic blood pressure (SBP) and diastolic blood pressure (DBP). This phenomenon has been used as the basis to design portable systems for continuously cuff-less blood pressure measurement, benefiting numerous people with heart conditions. However, the PTT-based blood pressure estimation may not be sufficiently accurate because the regulation of blood pressure within the human body is a complex, multivariate physiological process.

An exploratory study on a chest-worn computer for evaluation of diet, physical activity and lifestyle.

Recently, wearable computers have become new members in the family of mobile electronic devices, adding new functions to those provided by smart-phones and tablets. As "always-on" miniature computers in the personal space, they will play increasing roles in the field of healthcare. In this work, we present our development of eButton, a wearable computer designed as a personalized, attractive, and convenient chest pin in a circular shape.

Design of a Wireless EEG System for Point-of-Care Applications.

This study aims to develop a wireless EEG system to provide critical point-of-care information about brain electrical activity. A novel dry electrode, which can be installed rapidly, is used to acquire EEG from the scalp. A wireless data link between the electrode and a data port (i.

A low-impedance, skin-grabbing, and gel-free EEG electrode.

Inspired by the extraordinary object grabbing ability of certain insects (e.g., a grasshopper), we have developed a novel dry EEG electrode, called the skin screw electrode.

Early major neurologic complications after lung transplantation: incidence, risk factors, and outcome.

Background: Early major neurologic complications after lung transplantation represent a major source of morbidity for patients and compromise their quality of life; however, the mechanisms underlying neurologic complications and their impact on outcomes in lung transplantation remain largely unknown.

Methods: Patients who received lung transplants at our institution between January 2004 and December 2010 were identified (n=759). Data on complications including occurrence, timing, management, and outcome were extracted from our transplant database and medical record review.

Imaged based estimation of food volume using circular referents in dietary assessment.

Measuring food volume (portion size) is a critical component in both clinical and research dietary studies. With the wide availability of cell phones and other camera-ready mobile devices, food pictures can be taken, stored or transmitted easily to form an image based dietary record. Although this record enables a more accurate dietary recall, a digital image of food usually cannot be used to estimate portion size directly due to the lack of information about the scale and orientation of the food within the image.

Physical Activity Recognition Based on Motion in Images Acquired by a Wearable Camera.

A new technique to extract and evaluate physical activity patterns from image sequences captured by a wearable camera is presented in this paper. Unlike standard activity recognition schemes, the video data captured by our device do not include the wearer him/herself. The physical activity of the wearer, such as walking or exercising, is analyzed indirectly through the camera motion extracted from the acquired video frames.

A metabolic biofuel cell: conversion of human leukocyte metabolic activity to electrical currents.

An investigation of the electrochemical activity of human white blood cells (WBC) for biofuel cell (BFC) applications is described. WBCs isolated from whole human blood were suspended in PBS and introduced into the anode compartment of a proton exchange membrane (PEM) fuel cell. The cathode compartment contained a 50 mM potassium ferricyanide solution.

Recognizing physical activity from ego-motion of a camera.

A new image based activity recognition method for a person wearing a video camera below the neck is presented in this paper. The wearable device is used to capture video data in front of the wearer. Although the wearer never appears in the video, his or her physical activity is analyzed and recognized using the recorded scene changes resulting from the motion of the wearer.

Automatic detection of dining plates for image-based dietary evaluation.

An automatic detector that finds circular dining plates in chronically recorded images or videos is reported for the study of food intake and obesity. We first detect edges from input images. After a number of processing steps that convert edges into curves, arc filtering and grouping algorithms are applied.

Novel hydrogel-based preparation-free EEG electrode.

The largest obstacles to signal transduction for electroencephalography (EEG) recording are the hair and the epidermal stratum corneum of the skin. In typical clinical situations, hair is parted or removed, and the stratum corneum is either abraded or punctured using invasive penetration devices. These steps increase preparation time, discomfort, and the risk of infection.

Temporal postural synergies of the hand in rapid grasping tasks.

Postural synergies of the hand have been widely proposed in the literature, but only a few attempts were made to visualize temporal postural synergies, i.e., profiles of postural synergies varying over time.

Wireless energy transfer platform for medical sensors and implantable devices.

Witricity is a newly developed technique for wireless energy transfer. This paper presents a frequency adjustable witricity system to power medical sensors and implantable devices. New witricity resonators are designed for both energy transmission and reception.

Magnetoencephalographic imaging of deep corticostriatal network activity during a rewards paradigm.

The human rewards network is a complex system spanning both cortical and subcortical regions. While much is known about the functions of the various components of the network, research on the behavior of the network as a whole has been stymied due to an inability to detect signals at a high enough temporal resolution from both superficial and deep network components simultaneously. In this paper, we describe the application of magnetoencephalographic imaging (MEG) combined with advanced signal processing techniques to this problem.

Skin-electrode circuit model for use in optimizing energy transfer in volume conduction systems.

The X-Delta model for through-skin volume conduction systems is introduced and analyzed. This new model has advantages over our previous X model in that it explicitly represents current pathways in the skin. A vector network analyzer is used to take measurements on pig skin to obtain data for use in finding the model's impedance parameters.

Time encoding and reconstruction of multichannel data by brain implants using asynchronous sigma delta modulators.

Recently, information technology and microelectronics have enabled implanting miniature and highly intelligent devices within the brain for in-vitro diagnostic and therapeutic functions. Power and physical size constraints of these devices necessitate novel signal processing methods. In this paper we investigate an effective data acquisition and reconstruction method for brain implants based on Asynchronous Sigma Delta Modulators (ASDMs).

Dimensionality reduction in control and coordination of the human hand.

The concept of kinematic synergies is proposed to address the dimensionality reduction problem in control and coordination of the human hand. This paper develops a method for extracting kinematic synergies from joint-angular-velocity profiles of hand movements. Decomposition of a limited set of synergies from numerous movements is a complex optimization problem.

Spatial filtering of MEG signals for user-specified spherical regions.

We introduce a spatial filtering method in the spherical harmonics domain for constraining magnetoencephalographic (MEG) multichannel measurements to any user-specified spherical region of interest (ROI) inside the head. The method relies on a linear transformation of the signal space separation inner coefficients that represent the MEG signal generated by sources located inside the head. The spatial filtering is achieved effectively by constructing a spherical harmonics basis vector that is dependent on the center of the targeted ROI and it does not require any discrete division of the headspace into grids like the traditional MEG spatial filtering approaches.

Information capacity of the thumb and the index finger in communication.

Due to its large number of degrees of freedom and extensive connection to the brain, the human hand has been used to create channels of communication for a variety of human-machine systems. However, a fundamental question about the hand channel is still unanswered: what is its information capacity? This study aims to provide quantitative indication of effectiveness of the hand as a communication channel. We estimated that per gesture, the thumb and the index finger may deliver at most 10 and 7 bits of information, respectively.

Inherent bimanual postural synergies in hands.

This paper presents a numerical approach to prove the existence of inherent bimanual postural synergies while performing actions with two hands. Five subjects were tested in two different tasks. The first task was a well coordinated task where each subject screwed nut and bolt using one or both hands.