An up-to-date & curated list of Awesome IMU-based Human Activity Recognition(Ubiquitous Computing) papers, methods & resources. Please note that most of the collections of researches are mainly based on IMU data.
Many thanks to the useful publications and repos: Jingdong Wang, Awesome-Deep-Vision, Awesome-Deep-Learning-Papers, Awesome-Self-Supervised-Learning, Awesome-Semi-Supervised-Learning and Awesome-Crowd-Counting.
Please feel free to contribute this list.
- IJCAI, ACM MultiMedia, AAAI, KDD, ICDM, TKDE, TIP, TNNLS, TPAMI, TMM, Pattern Recognition, AI, Nature Communication, ICPR, Sensors, Ubicomp(IMWUT Journal)
- mHealth [link]
- Opportunity [link]
- PAMAP2 [link]
- GOTOV [link]
- REALDISP [link]
- UCIDSADS [link]
- MMAct [link]
- TotalCapture [link]
- WISDM [link]
- MotionSense [link]
- MobiAct [link]
- Fenland [link]
- Salad 50 [link]
- DIP [link]
- LARa [link]
- Large-Scale/Diverse Dataset Research
- Multi-Modality: sensor-vision, sensor-skeleton, sensor-3DPose, Sensor-Motion
- window selection
- Generative Model: e.g., cross modality data generation, IMU2Skeleton
- Handling the NULL-Class problem
- Open-World, Real-World: complex/non-repetitive activities
- Advanced model
- Data-cental: active learning, unsupervised learning, semi-supervised learning, self-supervised learning
- Actiion Segmentation
- Are the existing settings/models reliable?
- Graph Representation
- Motion-Capture, Kinetic
- Privacy related
- Interpretability
- Data Imbalance
- Domain Adaptation
- Fine-Grained
- Multi-Label
- Federated Learning
- Ensemble
- Knowledge Integragation/distillation
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A Survey on Deep Learning for Human Activity Recognition (ACM Computing Surveys (CSUR)) [paper]
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Applying Machine Learning for Sensor Data Analysis in Interactive Systems: Common Pitfalls of Pragmatic Use and Ways to Avoid Them (ACM Computing Surveys (CSUR)) [paper]
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[DL4SAR] Deep Learning for Sensor-based Activity Recognition: A Survey (Pattern Recognition Letters) [paper][code]
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Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges, and Opportunities (ACM Computing Surveys (CSUR)) [paper]
- LiteHAR: LIGHTWEIGHT HUMAN ACTIVITY RECOGNITION FROM WIFI SIGNALS WITH RANDOM CONVOLUTION KERNELS
- Zero-Shot Learning for IMU-Based Activity Recognition Using Video Embeddings
- Deep Transfer Learning with Graph Neural Network for Sensor-Based Human Activity Recognition
- Meta-learning meets the Internet of Things: Graph prototypical models for sensor-based human activity recognition
- Federated Multi-Task Learning
- Unsupervised Human Activity Recognition Using the Clustering Approach: A Review
- Hierarchical Self Attention Based Autoencoder for Open-Set Human Activity Recognition
- Assessing the State of Self-Supervised Human Activity Recognition using Wearables
- ROBUST AND EFFICIENT UNCERTAINTY AWARE BIOSIGNAL CLASSIFICATION VIA EARLY EXIT ENSEMBLES
- Machine learning detects altered spatial navigation features in outdoor behaviour of Alzheimer’s disease patients
- Evaluating Contrastive Learning on Wearable Timeseries for Downstream Clinical Outcomes
- Segmentation-free Heart Pathology Detection Using Deep Learning
- Anticipatory Detection of Compulsive Body-focused Repetitive Behaviors with Wearables
- Assessing the State of Self-Supervised Human Activity Recognition using Wearables
- Method and system for automatic extraction of virtual on-body inertial measurement units
- Enhancing the Security & Privacy of Wearable Brain-Computer Interfaces
- What Makes Good Contrastive Learning on Small-Scale Wearable-based Tasks?
- Detecting Smartwatch-Based Behavior Change in Response to a Multi-Domain Brain Health Intervention
- ColloSSL: Collaborative Self-Supervised Learning for Human Activity Recognition
- Multi-scale Deep Feature Learning for Human Activity Recognition Using Wearable Sensors
- Improving Wearable-Based Activity Recognition Using Image Representations
- Multi-sensor information fusion based on machine learning for real applications in human activity recognition: State-of-the-art and research challenges
- A recurrent neural network architecture to model physical activity energy expenditure in older people
- Application of artificial intelligence in wearable devices: Opportunities and challenges
- A Close Look into Human Activity Recognition Models using Deep Learning
- YONO: Modeling Multiple Heterogeneous Neural Networks on Microcontrollers
- CogAx: Early Assessment of Cognitive and Functional Impairment from Accelerometry
- Deep Temporal Conv-LSTM for Activity Recognition
- Human Activity Recognition from Wearable Sensor Data Using Self-Attention
- Combined deep centralized coordinate learning and hybrid loss for human activity recognition
- Real-time human activity recognition using conditionally parametrized convolutions on mobile and wearable devices
- Proposing a Fuzzy Soft‐max‐based classifier in a hybrid deep learning architecture for human activity recognition
- HAR-GCNN: Deep Graph CNNs for Human Activity Recognition From Highly Unlabeled Mobile Sensor Data
- Sensor-based human activity recognition using fuzzified deep CNN architecture with λmax method
- WearRF-CLA: Continuous Location Authentication with Wrist Wearables and UHF RFID
- Non-Bayesian Out-of-Distribution Detection Applied to CNN Architectures for Human Activity Recognition
- Improving the Performance of Open-Set Classification in Human Activity Recognition by Applying a Residual Neural Network Architecture
- A Review on Topological Data Analysis in Human Activity Recognition
- UBIWEAR: An End-To-End Framework for Intelligent Physical Activity Prediction With Machine and Deep Learning
- High-Precision and Personalized Wearable Sensing Systems for Healthcare Applications
- ColloSSL: Collaborative Self-Supervised Learning for Human Activity Recognition
- DANA: Dimension-Adaptive Neural Architecture
- DeXAR: Deep Explainable Sensor-Based Activity Recognition in Smart-Home Environments
- Latent Independent Excitation for Generalizable Sensor-based Cross-Person Activity Recognition
- The Severity Prediction of The Binary And Multi-Class Cardiovascular Disease -- A Machine Learning-Based Fusion Approach
- An Unsupervised User Adaptation Model for Multiple Wearable Sensors Based Human Activity Recognition
- Machine Learning on Clinical Time Series: Classification and Representation Learning
- Learning Disentangled Behaviour Patterns for Wearable-based Human Activity Recognition
- What Makes Good Contrastive Learning on Small-scale Wearable-based Tasks?
- Leveraging Activity Recognition to Enable Protective Behavior Detection in Continuous Data,
- IMU2Doppler: Cross-Modal Domain Adaptation for Doppler-based Activity Recognition Using IMU Data
- A CNN-based Human Activity Recognition System Combining a Laser Feedback Interferometry Eye Movement Sensor and an IMU for Context-aware Smart Glasses
- Winect: 3D Human Pose Tracking for Free-form Activity Using Commodity WiFi
- Zero-Shot Learning for IMU-Based Activity Recognition Using Video Embeddings
- KATN: Key Activity Detection via Inexact Supervised Learning
- Fusing Visual and Inertial Sensors with Semantics for 3D Human Pose Estimation
- Multi-gat: A graphical attention-based hierarchical multimodal representation learning approach for human activity recognition
- Semantics-aware adaptive knowledge distillation for sensor-to-vision action recognition
- Human action recognition from various data modalities: A review
- Eldersim: A synthetic data generation platform for human action recognition in eldercare applications
- Home action genome: Cooperative compositional action understanding
- Cross-modal Knowledge Distillation for Vision-to-Sensor Action Recognition
- Sensor-Augmented Egocentric-Video Captioning with Dynamic Modal Attention
- Disentanglement Approach for Video Action Recognition
- Fusion-GCN: Multimodal Action Recognition using Graph Convolutional Networks
- Meta-learning meets the Internet of Things: Graph prototypical models for sensor-based human activity recognition
- Human Activity Recognition Based on Wearable Sensor Data: A Standardization of the State-of-the-Art
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Approaching the Real-World: Supporting Activity Recognition Training with Virtual IMU Data [paper]
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Can You See It? Good, So We Can Sense It! [paper]
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An Ensemble of ConvTransformer Networks for the Sussex-Huawei Locomotion-Transportation (SHL) Recognition Challenge [paper]
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Fast Deep Neural Architecture Search for Wearable Activity Recognition by Early Prediction of Converged Performance [paper]
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Human Activity Recognition Based on Acceleration Data From Smartphones Using HMMs [paper]
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On the Role of Context Length for Feature Extraction and Sequence Modeling in Human Activity Recognition [paper]
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ObscureNet: Learning Attribute-invariant Latent Representation for Anonymizing Sensor Data [paper]
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SenseCollect: We Need Efficient Ways to Collect On-body Sensor-based Human Activity Data! [paper]
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Self-supervised Learning for Reading Activity Classification [paper]
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Approaching the Real-World: Supporting Activity Recognition Training with Virtual IMU Data [paper]
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Reducing Muscle Activity when Playing Tremolo by Using Electrical Muscle Stimulation to Learn Efficient Motor Skills [paper]
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Pushing the Limits of Long Range Wireless Sensing with LoRa [paper]
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CardiacWave: A mmWave-based Scheme of Non-Contact and High-Definition Heart Activity Computing [paper]
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Multimodal Federated Learning [paper]
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A Deep Learning-Based Framework for Human Activity Recognition in Smart Homes [paper]
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Interactive Hybrid Intelligence Systems for Human-Ai/Robot Collaboration: Improving the Practices of Physical Stroke Rehabilitation [paper]
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Continual Activity Recognition with Generative Adversarial Networks [paper]
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A multibranch CNN-BiLSTM model for human activity recognition using wearable sensor data [paper]
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Unsupervised User Adaptation Model for Multiple Wearable Sensors Based Human Activity Recognition [paper]
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ClusterFL: A Similarity-Aware Federated Learning System for Human Activity Recognition (MobiSys) [paper]
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Improving Deep Learning for HAR with shallow LSTMs (ISWC/ubicomp) [paper]
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Contrastive Predictive Coding for Human Activity Recognition (IMWUT/ubicomp) [paper]
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Leveraging Activity Recognition to Enable Protective Behavior Detection in Continuous Data (IMWUT/ubicomp) [paper]
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Watching Your Phone's Back: Gesture Recognition by Sensing Acoustical Structure-borne Propagation (IMWUT/ubicomp) [paper]
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ApneaDetector: Detecting Sleep Apnea with Smartwatches (IMWUT/ubicomp) [paper]
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NeckFace: Continuously Tracking Full Facial Expressions on Neck-mounted Wearables (IMWUT/ubicomp) [paper]
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We Hear Your PACE: Passive Acoustic Localization of Multiple Walking Persons (IMWUT/ubicomp) [paper]
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mTeeth: Identifying Brushing Teeth Surfaces Using Wrist-Worn Inertial Sensors (IMWUT/ubicomp) [paper]
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Acoustic-based Upper Facial Action Recognition for Smart Eyewear (IMWUT/ubicomp) [paper]
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Two-Stream Convolution Augmented Transformer for Human Activity Recognition (AAAI2021) [paper]
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Unsupervised Human Activity Representation Learning with Multi-task Deep Clustering (IMWUT/ubicomp) [paper]
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Attend and Discriminate: Beyond the State-of-the-Art for Human Activity Recognition Using Wearable Sensors (IMWUT/ubicomp) [paper]
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SelfHAR: Improving Human Activity Recognition through Self-training with Unlabeled Data (IMWUT/ubicomp) [paper]
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Latent Independent Excitation for Generalizable Sensor-based Cross-Person Activity Recognition (AAAI 2021) [paper]
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Weakly-Supervised Sensor-based Activity Segmentation and Recognition via Learning from Distributions (Artificial Intelligence (AIJ)) [paper]
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GIobalFusion: A Global Attentional Deep Learning Framework for Multisensor Information Fusion (IMWUT/ubicomp) [paper]
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METIER: A Deep Multi-Task Learning Based Activity and User Recognition Model Using Wearable Sensors (IMWUT/ubicomp) [paper]
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Instance-Wise Dynamic Sensor Selection for Human Activity Recognition (AAAI 2020) [paper]
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Cross-Dataset Activity Recognition via Adaptive Spatial-Temporal Transfer Learning (IMWUT/ubicomp) [paper]
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MARS: Mixed Virtual and Real Wearable Sensors for Human Activity Recognition with Multi-Domain Deep Learning Model [arXiv]
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Towards Deep Clustering of Human Activities from Wearables (ISWC/ubicomp) [paper]
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[UDA4HAR] A Systematic Study of Unsupervised Domain Adaptation for Robust Human-Activity Recognition (IMWUT/ubicomp) [paper]
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Adversarial Multi-view Networks for Activity Recognition (IMWUT/ubicomp) [paper]
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Weakly Supervised Multi-Task Representation Learning for Human Activity Analysis Using Wearables (IMWUT/ubicomp) [paper]
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[IMUTube] IMUTube: Automatic Extraction of Virtual on-body Accelerometry from Video for Human Activity Recognition (IMWUT/ubicomp) [paper]
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Robust Unsupervised Factory Activity Recognition with Body-worn Accelerometer Using Temporal Structure of Multiple Sensor Data Motifs (IMWUT/ubicomp) [paper]
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Masked reconstruction based self-supervision for human activity recognition (ISWC/ubicomp) [paper]
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Digging deeper: towards a better understanding of transfer learning for human activity recognition with Body-worn Accelerometer Using Temporal Structure of Multiple Sensor Data Motifs (ISWC/ubicomp) [paper]
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IndRNN based long-term temporal recognition in the spatial and frequency domain (ISWC/ubicomp) [paper]
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Tackling the SHL challenge 2020 with person-specific classifiers and semi-supervised learning (ISWC/ubicomp) [paper]
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DenseNetX and GRU for the sussex-huawei locomotion-transportation recognition challenge (ISWC/ubicomp) [paper]
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A Novel Distribution-Embedded Neural Network for Sensor-Based Activity Recognition (IJCAI) [paper][code]
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Learning Bodily and Temporal Attention in Protective Movement Behavior Detection
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[AttnSense] AttnSense: Multi-level Attention Mechanism For Multimodal Human Activity Recognition (IJCAI) [paper]
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Multi-agent Attentional Activity Recognition (IJCAI) [paper][code]
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Distribution-based Semi-Supervised Learning for Activity Recognition (AAAI) [paper][code]
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On the Role of Features in Human Activity Recognition (ISWC/ubicomp) [paper]
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Handling Annotation Uncertainty in Human Activity Recognition (ISWC/ubicomp) [paper]
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Leveraging Active Learning and Conditional Mutual Information to Minimize Data Annotation in Human Activity Recognition (IMWUT/ubicomp) [paper]
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[Vision2Sensor] Vision2Sensor: Knowledge Transfer Across Sensing Modalities for Human Activity Recognition (IMWUT/ubicomp) [paper]
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How Does a Nation Walk? Interpreting Large-Scale Step Count Activity with Weekly Streak Patterns (IMWUT/ubicomp) [paper]
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Understanding and Improving Recurrent Networks for Human Activity Recognition by Continuous Attention (ISWC/ubicomp) [paper]
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On specialized window lengths and detector based human activity recognition (ISWC/ubicomp) [paper]
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Adding structural characteristics to distribution-based accelerometer representations for activity recognition using wearables (ISWC/ubicomp) [paper]
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On Attention Models for Human Activity Recognition (ISWC/ubicomp) [paper]
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[AROMA] AROMA: A Deep Multi-Task Learning Based Simple and Complex Human Activity Recognition Method Using Wearable Sensors (IMWUT/ubicomp) [paper]
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[EnsemblesLSTM] Ensembles of Deep LSTM Learners for Activity Recognition using Wearables (IMWUT/ubicomp) [paper] [Tensorflow]
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Deep Learning for Sensor-based Activity Recognition: A Survey (Pattern Recognition Letters) [paper]
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Activity Recognition for Quality Assessment of Batting Shots in Cricket using a Hierarchical Representation (IMWUT/ubicomp) [paper]
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Label Propagation: An Unsupervised Similarity Based Method for Integrating New Sensors in Activity Recognition Systems (IMWUT/ubicomp) [paper]
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CNN-based sensor fusion techniques for multimodal human activity recognition (ISWC/ubicomp) [paper]
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Learning from less for better: semi-supervised activity recognition via shared structure discovery (ubicomp) [paper]
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Wearable sensor based multimodal human activity recognition exploiting the diversity of classifier ensemble (ubicomp) [paper]
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Beyond activity recognition: skill assessment from accelerometer data (ubicomp) [paper]
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I did not smoke 100 cigarettes today!: avoiding false positives in real-world activity recognition (ubicomp) [paper]
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Let's (not) stick together: pairwise similarity biases cross-validation in activity recognition (ubicomp) [paper]
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Improved activity recognition by using enriched acceleration data (ubicomp) [paper]
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A field study comparing approaches to collecting annotated activity data in real-world settings (ubicomp) [paper]
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Personalization revisited: a reflective approach helps people better personalize health services and motivates them to increase physical activity (ubicomp) [paper]
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MONITORING HOUSEHOLD ACTIVITIES AND USER LOCATION WITH A CHEAP, UNOBTRUSIVE THERMAL SENSOR ARRAY (ubicomp) [paper]
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Connecting personal-scale sensing and networked community behavior to infer human activities (ubicomp) [paper]
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Using electrodermal activity to recognize ease of engagement in children during social interactions (ubicomp) [paper]
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Fine-Grained Sharing of Sensed Physical Activity: A Value Sensitive Approach (ubicomp) [paper]
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Towards zero-shot learning for human activity recognition using semantic attribute sequence model (ubicomp) [paper]
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Personalized mobile physical activity recognition (ubicomp) [paper]
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A Hybrid Unsupervised/Supervised Model for Group Activity Recognition (ubicomp) [paper]
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Confidence-based Multiclass AdaBoost for Physical Activity Monitoring (ubicomp) [paper]
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An exploration with online complex activity recognition using cellphone accelerometer (ubicomp) [paper]
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[UniPad] UniPad: Orchestrating collaborative activities through shared tablets and an integrated wall display (ubicomp) [paper]
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Human Activity Recognition Using Heterogeneous Sensors (ubicomp) [paper]
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A probabilistic ontological framework for the recognition of multilevel human activities (ubicomp) [paper]
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Ubiquitous support for midwives to leverage daily activities (ubicomp) [paper]
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Combining Embedded Accelerometers with Computer Vision for Recognizing Food Preparation Activities (ubicomp) [paper]
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A Spark Of Activity: Exploring Information Art As Visualization For Physical Activity (ubicomp) [paper]
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[BodyScope] BodyScope: A Wearable Acoustic Sensor for Activity Recognition (ubicomp) [paper]
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An Integrated Framework for Human Activity Classification (ubicomp) [paper]
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The Place for Ubiquitous Computing in Schools: Lessons Learned from a School-Based Intervention for Youth Physical Activity (ubicomp) [paper]
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[CSN] Enabling Large-scale Human Activity Inference on Smartphones using Community Similarity Networks (ubicomp) [paper]
- Using Wearable Activity Type Detection to Improve Physical Activity Energy Expenditure Estimation (ubicomp) [paper]