Publications related to Smartphone

Understanding and Enhancing Digital Wellbeing Dimensions: Empirical Studies on Smartphone Usage Patterns and Recommendations of Micro-Informative Content

Digital technology has become an integral part of our lives, offering various benefits from communication and entertainment to education and productivity. However, its pervasive use has also raised concerns about its potential negative impact on users' wel ...

EPFL2024

Generalization and Personalization of Machine Learning for Multimodal Mobile Sensing in Everyday Life

Lakmal Buddika Meegahapola

A range of behavioral and contextual factors, including eating and drinking behavior, mood, social context, and other daily activities, can significantly impact an individual's quality of life and overall well-being. Therefore, inferring everyday life aspe ...

EPFL2024

TEEzz: Fuzzing Trusted Applications on COTS Android Devices

Mathias Josef Payer, Marcel Busch

Security and privacy-sensitive smartphone applications use trusted execution environments (TEEs) to protect sensitive operations from malicious code. By design, TEEs have privileged access to the entire system but expose little to no insight into their inn ...

IEEE COMPUTER SOC2023

Tumescense monitoring system for diagnosing erectile dysfunction and methods of use

Nikolaos Stergiopoulos, Rodrigo Araujo Fraga Da Silva

Systems and methods for monitoring penile tumescence are provided that overcome the drawbacks of previously known systems by providing a wearable formed of a flexible and elastic tube having a plurality of sensors disposed on or embedded within it, the wea ...

2023

EOS: Efficient Private Delegation of zkSNARK Provers

Alessandro Chiesa, Yinuo Zhang

Succinct zero knowledge proofs (i.e. zkSNARKs) are powerful cryptographic tools that enable a prover to convince a verifier that a given statement is true without revealing any additional information. Their attractive privacy properties have led to much ac ...

Usenix Assoc2023

Uncovering personalized glucose responses and circadian rhythms from multiple wearable biosensors with Bayesian dynamical modeling

Felix Naef, Nicholas Edward Phillips

Wearable biosensors and smartphone applications can measure physiological variables over multiple days in free-living conditions. We measure food and drink ingestion, glucose dynamics, physical activity, heart rate (HR), and heart rate variability (HRV) in ...

CELL PRESS2023

Data Privacy Concerns as a Source of Resistance to Complete Mobile Data Collection Tasks Via a Smartphone App

Daniel Gatica-Perez

Smartphones present many interesting opportunities for survey research, particularly through the use of mobile data collection applications (apps). There is still much to learn, however, about how to integrate apps in general population surveys. Recent stu ...

OXFORD UNIV PRESS INC2022

Simulation Of New Methods Using Applications Which Exflitrate Data From Android Phones

Maria-Alexandra Paun

Nowadays mobile phones have become indispensable, as they have been endowed with many of the capabilities that a user was able to achieve previously with the help of PCs only. Among the functions that mobile phones perform we identify audio and video calls ...

POLYTECHNIC UNIV BUCHAREST2022

Sensing Eating Events in Context: A Smartphone-Only Approach

Daniel Gatica-Perez, Lakmal Buddika Meegahapola

While the task of automatically detecting eating events has been examined in prior work using various wearable devices, the use of smartphones as standalone devices to infer eating events remains an open issue. This paper proposes a framework that infers e ...

2022

Groove: Flexible Metadata-Private Messaging

Ludovic Barman, David Lazar

Metadata-private messaging designs that scale to support millions of users are rigid: they limit users to a single device that is online all the time and transmits on short regular intervals, and require users to choose precisely when each of their buddies ...

Usenix Assoc2022

Smartphone-Based Visual Inspection with Acetic Acid: An Innovative Tool to Improve Cervical Cancer Screening in Low-Resource Setting

Roser Vinals Terres

Visual inspection with acetic acid (VIA) is recommended by theWorld Health Organization for primary cervical cancer screening or triage of human papillomavirus-positive women living in low-resource settings. Nonetheless, traditional VIA with the naked-eye ...

MDPI2022

Motion Style Transfer: Modular Low-Rank Adaptation for Deep Motion Forecasting

Alexandre Massoud Alahi, Yuejiang Liu, Parth Ashit Kothari, Danya Li

Deep motion forecasting models have achieved great success when trained on a massive amount of data. Yet, they often perform poorly when training data is limited. To address this challenge, we propose a transfer learning approach for efficiently adapting p ...

2022

A Battery-Free Wireless Smart Sensor platform with Bluetooth Low Energy Connectivity for Smart Agriculture

Catherine Dehollain, Roberto La Rosa

Smart agriculture systems, which integrate sensors and data analysis into agricultural production processes, are increasingly proving an effective solution for reducing food production waste, yield production increase, and product quality improvement. In t ...

IEEE2022

3D printing of elastomeric mechanical sensors designed for human motion monitoring

Ryan Mitchell van Dommelen

In this thesis several advances are made to the emerging field of 3D printed mechanical sensors. Techniques and processes were developed to enable the integration of highly conductive, and capacitive and piezoresistive sensing features embedded within 3D p ...

EPFL2022

On the Effectiveness of Time Travel to Inject COVID-19 Alerts

Serge Vaudenay, Martin Vuagnoux

Digital contact tracing apps allow to alert people who have been in contact with people who may be contagious. The Google/Apple Exposure Notification (GAEN) system is based on Bluetooth proximity estimation. It has been adopted by many countries around the ...

Springer, Cham2021

The Effects of Time-Restricted Eating versus Standard Dietary Advice on Weight, Metabolic Health and the Consumption of Processed Food: A Pragmatic Randomised Controlled Trial in Community-Based Adults

Felix Naef, Nicholas Edward Phillips

Weight loss is key to controlling the increasing prevalence of metabolic syndrome (MS) and its components, i.e., central obesity, hypertension, prediabetes and dyslipidaemia. The goals of our study were two-fold. First, we characterised the relationships b ...

2021

DepthInSpace: Exploitation and Fusion of Multiple Video Frames for Structured-Light Depth Estimation

François Fleuret, Camilla Carta

We present DepthInSpace, a self-supervised deep-learning method for depth estimation using a structured-light camera. The design of this method is motivated by the commercial use case of embedded depth sensors in nowadays smartphones. We first propose to u ...

IEEE2021

Ten seconds of my nights: Exploring methods to measure brightness, loudness and attendance and their associations with alcohol use from video clips

Daniel Gatica-Perez, Skanda Muralidhar, Lakmal Buddika Meegahapola

Introduction Most evidence on associations between alcohol use behaviors and the characteristics of its social and physical context is based on self-reports from study participants and, thus, only account for their subjective impressions of the situation. ...

2021

A Low-noise CMOS SPAD Pixel with 12.1 ps SPTR and 3 ns Dead Time

Edoardo Charbon, Claudio Bruschini, Ming-Lo Wu, Francesco Gramuglia, Myung Jae Lee

In this paper, we present the first CMOS SPAD with performance comparable or better than that of the best custom SPADs, to date. The SPAD-based design, fully integrated in 180 nm CMOS technology, achieves a peak PDP of 55% at 480nm with a very broad spectr ...

2022

Hardware-oriented pruning and quantization of Deep Learning models to detect life-threatening arrhythmias

Alexandre Schmid, Lizeth Gonzalez Carabarin

Wearable solutions based on Deep Learning (DL) for real-time ECG monitoring are a promising alternative to detect life-threatening arrhythmias. However, DL models suffer of a large memory footprint, which hampers their adoption in portable technologies. Th ...

IEEE2021