Deniz Ekiz

Deniz Ekiz
Bogazici University · Department of Computer Engineering

PhDc

About

13
Publications
13,633
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
238
Citations
Introduction
Deep Learning, Machine Learning, Human Activity Recognition, Affective Computing, Wearable Computing
Education
January 2019 - January 2023
Bogazici University
Field of study
  • Computer Science
September 2016 - December 2018
Bogazici University
Field of study
  • Computer Science

Publications

Publications (13)
Article
Continuous high perceived workload has a negative impact on the individual's well-being. Prior works focused on detecting the workload with medical-grade wearable systems in restricted settings, and the effect of applying deep learning techniques for perceived workload detection in the wild settings is not investigated. We present an unobtrusive, c...
Article
The number of fitness tracker users increases every day. Most of the applications require authentication to protect privacy-preserving operations. Biometrics such as face images have been used widely as login tokens, but they have privacy issues. Moreover, occlusions like face masks used for COVID may reduce their effectiveness. Smartbands can trac...
Article
Full-text available
Stress is an inescapable element of the modern age. Instances of untreated stress may lead to a reduction in the individual’s health, well-being and socio-economic situation. Stress management application development for wearable smart devices is a growing market. The use of wearable smart devices and biofeedback for individualized real-life stress...
Article
Full-text available
An automatic stress detection system that uses unobtrusive smart bands will contribute to human health and wellbeing by alleviating the effects of high stress levels. However, there are a number of challenges for detecting stress in unrestricted daily life which results in lower performances of such systems when compared to semi-restricted and labo...
Article
Full-text available
The use of cloud services that process privacy-sensitive information such as digital banking, pervasive healthcare, smart home applications requires an implicit continuous authentication solution, which will make these systems less vulnerable to the spoofing attacks. Physiological signals can be used for continuous authentication due to their uniqu...
Article
Full-text available
Researchers strive hard to develop effective ways to detect and cope with enduring highlevel daily stress as early as possible to prevent serious health consequences. Although research has traditionally been conducted in laboratory settings, a set of new studies have recently begun to be conducted in ecological environments with unobtrusive wearabl...
Article
Full-text available
Chronic stress leads to poor well-being, and it has effects on life quality and health. Society may have significant benefits from an automatic daily life stress detection system using unobtrusive wearable devices using physiological signals. However, the performance of these systems is not sufficiently accurate when they are used in unrestricted d...
Preprint
Full-text available
The use of cloud services that process privacy-sensitive information such as digital banking, pervasive healthcare, smart home applications require an implicit continuous authentication solution which will make these systems less vulnerable to the spoofing attacks. Physiological signals can be used for continuous authentication due to their persona...
Preprint
Full-text available
Continuous high perceived workload has a negative impact on the individual's well-being. Prior works focused on detecting the workload with medical-grade wearable systems in the restricted settings, and the effect of applying deep learning techniques for perceived workload detection in the wild settings is not investigated. We present an unobtrusiv...
Article
Full-text available
The negative effects of mental stress on human health has been known for decades. High-level stress must be detected at early stages to prevent these negative effects. After the emergence of wearable devices that could be part of our lives, researchers have started detecting extreme stress of individuals with them during daily routines. Initial exp...
Thesis
Full-text available
In the last decades, most of the diseases in modern society are caused by stress. This is the reason researchers want to detect and alleviate stress in daily life as early as possible. With the advance of technology, smartphones, smartbands, watches have become integral items of our daily lives. The research question that whether detecting stress w...
Presentation
Full-text available
In this study, we deployed a stress detection framework with commercial smartwatches and smart wristbands in ILKYAR summer school event which took place in Boğaziçi University. In this event, teachers from public schools from different cities are gathered and attend a series of seminars from university lecturers. This year, thirty-six teachers atte...
Conference Paper
Full-text available
We present a smartwatch application that recognizes important sign sentences. We make use of modern smart watches like Samsung Gear that are equipped with inbuilt sensors including accelerometer, gyroscope and magnetometer. We show how well a smartwatch can recognize important sign sentences. We have implemented a smartwatch app that collects 3d ac...

Network

Cited By