scispace - formally typeset
A

Andrius Dzedzickis

Researcher at Vilnius Gediminas Technical University

Publications -  45
Citations -  381

Andrius Dzedzickis is an academic researcher from Vilnius Gediminas Technical University. The author has contributed to research in topics: Computer science & Engineering. The author has an hindex of 5, co-authored 31 publications receiving 127 citations.

Papers
More filters
Journal ArticleDOI

Human Emotion Recognition: Review of Sensors and Methods.

TL;DR: This paper covers a few classes of sensors, using contactless methods as well as contact and skin-penetrating electrodes for human emotion detection and the measurement of their intensity and proposes their classification.
Journal ArticleDOI

Polyethylene-Carbon Composite (Velostat®) Based Tactile Sensor

TL;DR: Evaluated characteristics of a force-sensitive material—polyethylene-carbon composite (Velostat®) by implementing this material into the design of the flexible tactile sensor, finding dependencies of the sensor’s sensitivity, hysteresis, response time, transversal resolution and deformation on applied compressive force promise a practical possibility to use this material for sensors with a single electrode pair or its matrix.
Journal ArticleDOI

Yeast-based microbial biofuel cell mediated by 9,10-phenantrenequinone

TL;DR: This research demonstrates the applicability of Baker yeast cells in the design of microbial biofuel cells by applying PQ as a redox mediator for yeast-based MFC improves electron transfer through the yeast cell membrane and cell wall towards electrode without any noticeable decrease of yeast cell viability.
Journal ArticleDOI

Wearable Feet Pressure Sensor for Human Gait and Falling Diagnosis.

TL;DR: In this paper, a fall detection system based on gait analysis can be very helpful, especially if sensors of this system are implemented inside the shoes without causing a sensible discomfort for the user.
Journal ArticleDOI

Road Surface Profile Synthesis: Assessment of Suitability for Simulation

TL;DR: In this article, the authors compared the usability and ISO-compatibility of three methods: white noise filtration, sinusoidal approximation, and moving average of white noise.