Aydin Farajidavar

A miniature bidirectional telemetry system for in vivo gastric slow wave recordings

Stomach contractions are initiated and coordinated by an underlying electrical activity (slow waves), and electrical dysrhythmias accompany motility diseases. Electrical recordings taken directly from the stomach provide the most valuable data, but face technical constraints. Serosal or mucosal electrodes have cables that traverse the abdominal wall, or a natural orifice, causing discomfort and possible infection, and restricting mobility. These problems motivated the development of a wireless system. The bidirectional telemetric system constitutes a front-end transponder, a back-end receiver and a graphical userinter face. The front-end module conditions the analogue signals, then digitizes and loads the data into a radio for transmission. Data receipt at the backend is acknowledged via a transceiver function. The system was validated in a bench-top study, then validated in vivo using serosal electrodes connected simultaneously to a commercial wired system. The front-end module was 35 × 35 × 27 mm3 and weighed 20 g. Bench-top tests demonstrated reliable communication within a distance range of 30 m, power consumption of 13.5 mW, and 124 h operation when utilizing a 560 mAh, 3 V battery. In vivo,slow wave frequencies were recorded identically with the wireless and wired reference systems (2.4 cycles min−1), automated activation time detection was modestly better for the wireless system (5% versus 14% FP rate), and signal amplitudes were modestly higher via the wireless system (462 versus 3 86μV; p<0.001). This telemetric system for slow wave acquisition is reliable,power efficient, readily portable and potentially implantable. The device will enable chronic monitoring and evaluation of slow wave patterns in animals and patients.0967-3334/

Multi-channel wireless mapping of gastrointestinal serosal slow wave propagation.

High‐resolution (HR) extracellular mapping allows accurate profiling of normal and dysrhythmic slow wave patterns. A current limitation is that cables traverse the abdominal wall or a natural orifice, risking discomfort, dislodgement or infection. Wireless approaches offer advantages, but a multi‐channel system is required, capable of recording slow waves and mapping propagation with high fidelity.

AndroRC: An Android remote control car unit for search missions

The AndroRC is a remote control car (RC) unit controlled by a smartphone running on an Android application. The car is meant to be used in search missions in the occurrence of natural disasters. It is developed to autonomously avoid obstacles that are not visible to the user driver. The RC unit is developed based on a Tamiya 70112 Buggy car chassis set with an extra servo motor added to provide the left and right directions. The RC is equipped with an ultrasonic distance sensor, a camera, a Bluetooth receiver, a Wi-Fi transmitter, two 9-V batteries and two Arduino microcontroller boards (UNO and MEGA). The Arduino MEGA controls the propulsion and direction, while the UNO processes the information received from the distance sensor to stop the RC at a pre-defined distance. The Android application uses the embedded orientation sensor on the smartphone to determine the four directions (forward, backward, left and right) intended by the user; hence, rotating the smartphone to different directions results in to the corresponding propulsion of the RC unit. The control commands are transmitted to the RC unit through the Bluetooth communication. The Android application also receives (via Wi-Fi) and displays the information from the camera in real-time. The AndroRC was characterized and examined on bench-top settings.

A wireless system for monitoring transcranial motor evoked potentials.

Intraoperative neurophysiological monitoring (IONM) is commonly used as an attempt to minimize neurological morbidity from operative manipulations. The goal of IONM is to identify changes in the central and peripheral nervous system function prior to irreversible damage. Intraoperative monitoring also has been effective in localizing anatomical structures, including peripheral nerves and sensorimotor cortex, which helps guide the surgeon during dissection. As part of IONM, transcranial motor evoked potentials (TcMEPs), and somatosensory evoked potentials (SSEPs) are routinely monitored. However, current wired systems are cumbersome as the wires contribute to the crowded conditions in the operating room and in doing so not only it limits the maneuverability of the surgeon and assistants, but also places certain demand in the total anesthesia required during surgery, due to setup preoperative time needed for proper electrode placement, due to the number and length of the wires, and critical identification of the lead wires needed for stimulation and recording. To address these limitations, we have developed a wireless TcMEP IONM system as a first step toward a multimodality IONM system. Bench-top and animal experiments in rodents demonstrated that the wireless method reproduced with high fidelity, and even increased the frequency bandwidth of the TcMEP signals, compared to wired systems. This wireless system will reduce the preoperative time required for IONM setup, add convenience for surgical staff, and reduce wire-related risks for patients during the operation.

Recognition and inhibition of dorsal horn nociceptive signals within a closed-loop system

We implemented an integrated system that can acquire neuronal signals from spinal cord dorsal horn neurons, wirelessly transmit the signals to a computer, and recognize the nociceptive signals from three different mechanical stimuli (brush, pressure and pinch). Positive peak detection method was chosen to distinguish between signal spikes. The inter spike intervals (ISIs) were calculated from the identified action potentials (APs) and fed into a numerical array called cluster. When the sum of the ISIs in the cluster reached a critical level, the program recognized the recorded signals as nociceptive inputs. The user has the flexibility to tune both the cluster size and critical threshold for individuals need to reach optimization in pain signal recognition. The program was integrated with a wireless neurostimulator to form a feedback loop to recognize and inhibit nociceptive signals.

On Inferring Browsing Activity on Smartphones via USB Power Analysis Side-Channel

In this paper, we show that public USB charging stations pose a significant privacy risk to smartphone users even when no data communication is possible between the station and the user’s mobile device. We present a side-channel attack that allows a charging station to identify which Webpages are loaded while the smartphone is charging. To evaluate this side-channel, we collected power traces of Alexa top 50 Websites on multiple smartphones under several conditions, including battery charging level, browser cache enabled/disabled, taps on the screen, Wi-Fi/LTE, TLS encryption enabled/disabled, time elapsed between collection of training and testing data, and location of the Website. The results of our evaluation show that the attack is highly successful: in many settings, we were able to achieve over 90% Webpage identification accuracy. On the other hand, our experiments also show that this side-channel is sensitive to some of the aforementioned conditions. For instance, when training and testing traces were collected 70 days apart, accuracies were as low as 2.2%. Although there are studies that show that power-based side-channels can predict browsing activity on laptops, this paper is unique, because it is the first to study this side-channel on smartphones, under smartphone-specific constraints. Further, we demonstrate that Websites can be correctly identified within a short time span of

An interoperable pillbox system for smart medication adherence

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Computational Modeling of A Fiber Wind-up

seconds, which is in contrast with prior work, which uses 15-s traces. This is important, because users typically spend less than 15 s on a Webpage.

IPLMS: An intelligent parking lot management system

We have designed and fabricated an interoperable system for medication adherence. The system is composed of a pillbox that wirelessly communicates with a computer application and a custom-made wristband. The system receives the information of taking specific medication from the user or caregiver, reminds the user to take the medication, monitors the users hand gesture during the medication intake and monitors the compartments of the pillbox for refilling purpose. The performance of the developed system was examined in various bench-top scenarios. The system has the potential to improve the existing systems by reminding the user to take the medication through the wristband, automatically collecting users hand gestures during the medication intake, and providing detailed information about the exisexistencetence of medication in the compartments of the pillbox.

A comprehensive method for magnetic sensor calibration: A precise system for 3-D tracking of the tongue movements

Wind-up, a condition related to chronic pain, is described traditionally as a frequency dependent increase in the excitability of sensory spinal cord neurons, evoked by electrical stimulation of small pain fibers. In this paper, we introduce a computational model on wind-up of large (Abeta) fibers, considering three major mechanisms of wind-up: 1) a feedforward mechanism causing Ca2+ entry, 2) a positive feedback, causing more Ca2+ entry, and 3) a feedforward due to sprouting of Abeta fibers towards the small pain fibers. Our model proposes three different ways for reducing wind-up and shows the most important way to treat the pain