mobile-sensing

MotionSense Dataset for Human Activity and Attribute Recognition ( time-series data generated by smartphone's sensors: accelerometer and gyroscope) (PMC Journal) (IoTDI'19)

A collection of datasets, papers, and resources for Generalizable Human Activity Recognition and IMU sensing.

A lite BERT-like representation model for IMU sensor data

An iOS framework that provides Mobile Sensing to your apps.

An Android framework that provides Mobile Sensing to your apps.

Contrastive Learning (SimCLR) for Human Activity Recognition

Official implementation of the pupillometry system called PupilSense proposed in the article "PupilSense: Detection of Depressive Episodes Through Pupillary Response in the Wild".

Improving Human Activity Recognition through Self-training with Unlabeled Data

Official implementation of the affective mobile sensing system called FacePsy proposed in the article "FacePsy: An Open-Source Affective Mobile Sensing System - Analyzing Facial Behavior and Head Gesture for Depression Detection in Naturalistic Settings".

A Cross-Platform System for Mobile Sensing

Mobile Android app for data collection in the wild: sensor measurements and self-reported labels describing the user's behavioral context.

Feature engineering on LivePeople dataset

This is the code repository for the paper "BenHAR: Benchmarking Self-Supervised Learning for Generalizable Sensor-based Activity Recognition".

A C# project to simulate and test a multiagent algorithm for finding multiple noisy radiation sources with spatial and communication constraints with an emulated environment. The algorithm tries to detect the source(s) of radiation with some robots in the monitoring fields. Each robot has a sensor mounted to detect the radiation concentration. T…

Code for "Blinder: End-to-end Privacy Protection in Sensing Systems via Personalized Federated Learning", ACM ToSN

Source code for paper "FaceListener: Recognizing Human Facial Expressions via Acoustic Sensing on Commodity Headphones"

Reproducible R code for the master's thesis "Toward causality in mobile sensing for depression," using sparse functional data analysis (FDA) and conditional independence testing on the StudentLife datasets.

The WHALE Mobile Sensing platform