520 citations · 1.1k across the 14 of their papers we have counts for
16 papers
Rondo: Unsupervised Discovery of Recurring Temporal Structure
Yingtian Shi, Ankith Chandra, Thomas Plötz
Many real-world time series data exhibit structural properties at multiple scales, from short, recurring units to complex sequences composed of these units. Unsupervised discovery…
Hierarchical Modeling of ICD Codes in EHR Foundation Models
Megha Thukral, Dong Gyun Kang, Rudra Pratap Singh +3
Electronic health record foundation models typically treat ICD diagnosis codes as flat tokens, overlooking the clinically meaningful hierarchical structure that captures disease fa…
TRACE: Temporal Reasoning over Context and Evidence for Activity Recognition in Smart Homes
Yingtian Shi, Abivishaq Balasubramanian, Jessica Herring +7
Human activity recognition (HAR) in smart homes remains challenging because many daily activities exhibit similar local sensor patterns, while minimally intrusive sensing provides…
Maintenance Required: Updating and Extending Bootstrapped Human Activity Recognition Systems for Smart Homes
Shruthi K. Hiremath, Thomas Ploetz
Developing human activity recognition (HAR) systems for smart homes is not straightforward due to varied layouts of the homes and their personalized settings, as well as idiosyncra…
Large Language Models Memorize Sensor Datasets! Implications on Human Activity Recognition Research
Harish Haresamudram, Hrudhai Rajasekhar, Nikhil Murlidhar Shanbhogue +1
The astonishing success of Large Language Models (LLMs) in Natural Language Processing (NLP) has spurred their use in many application domains beyond text analysis, including weara…
Transfer Learning in Human Activity Recognition: A Survey
Sourish Gunesh Dhekane, Thomas Ploetz
Sensor-based human activity recognition (HAR) has been an active research area, owing to its applications in smart environments, assisted living, fitness, healthcare, etc. Recently…
Know Thy Neighbors: A Graph Based Approach for Effective Sensor-Based Human Activity Recognition in Smart Homes
Srivatsa P, Thomas Plötz
There has been a resurgence of applications focused on Human Activity Recognition (HAR) in smart homes, especially in the field of ambient intelligence and assisted living technolo…
On the Benefit of Generative Foundation Models for Human Activity Recognition
Zikang Leng, Hyeokhyen Kwon, Thomas Plötz
In human activity recognition (HAR), the limited availability of annotated data presents a significant challenge. Drawing inspiration from the latest advancements in generative AI,…
Ubi-SleepNet: Advanced Multimodal Fusion Techniques for Three-stage Sleep Classification Using Ubiquitous Sensing
Bing Zhai, Yu Guan, Michael Catt +1
Sleep is a fundamental physiological process that is essential for sustaining a healthy body and mind. The gold standard for clinical sleep monitoring is polysomnography(PSG), base…
Towards Reliable, Automated General Movement Assessment for Perinatal Stroke Screening in Infants Using Wearable Accelerometers
Yan Gao, Yang Long, Yu Guan +3
Perinatal stroke (PS) is a serious condition that, if undetected and thus untreated, often leads to life-long disability, in particular Cerebral Palsy (CP). In clinical settings, P…
Assessing the quality of home detection from mobile phone data for official statistics
Maarten Vanhoof, Fernando Reis, Thomas Ploetz +1
Mobile phone data are an interesting new data source for official statistics. However, multiple problems and uncertainties need to be solved before these data can inform, support o…
Detecting home locations from CDR data: introducing spatial uncertainty to the state-of-the-art
Maarten Vanhoof, Fernando Reis, Zbigniew Smoreda +1
Non-continuous location traces inferred from Call Detail Records (CDR) at population scale are increasingly becoming available for research and show great potential for automated d…
On Attention Models for Human Activity Recognition
Vishvak S Murahari, Thomas Ploetz
Most approaches that model time-series data in human activity recognition based on body-worn sensing (HAR) use a fixed size temporal context to represent different activities. This…
Ensembles of Deep LSTM Learners for Activity Recognition using Wearables
Yu Guan, Thomas Ploetz
Recently, deep learning (DL) methods have been introduced very successfully into human activity recognition (HAR) scenarios in ubiquitous and wearable computing. Especially the pro…
Deep, Convolutional, and Recurrent Models for Human Activity Recognition using Wearables
Nils Y. Hammerla, Shane Halloran, Thomas Ploetz
Human activity recognition (HAR) in ubiquitous computing is beginning to adopt deep learning to substitute for well-established analysis techniques that rely on hand-crafted featur…
Augmenting Bag-of-Words: Data-Driven Discovery of Temporal and Structural Information for Activity Recognition
Vinay Bettadapura, Grant Schindler, Thomaz Plotz +1
We present data-driven techniques to augment Bag of Words (BoW) models, which allow for more robust modeling and recognition of complex long-term activities, especially when the st…