{"doi":"10.1145/3544793.3563423","title":"Excerpt of Auritus: An Open-Source Optimization Toolkit for Training and Development of Human Movement Models and Filters Using Earables","abstract":"Auritus is an extendable and open-source optimization toolkit designed to enhance and replicate earable applications. Auritus serves two primary functions. Firstly, Auritus handles data collection, pre-processing, and labeling tasks for creating customized earable datasets using graphical tools. The system includes an open-source dataset with 2.43 million inertial samples related to head and full-body movements, consisting of 34 head poses and 9 activities from 45 volunteers. Secondly, Auritus provides a tightly-integrated hardware-in-the-loop (HIL) optimizer and TinyML interface to develop lightweight and real-time machine-learning (ML) models for activity detection and filters for head-pose tracking. Auritus recognizes activities with 91% leave 1-out test accuracy (98% test accuracy) using real-time models as small as 6-13 kB. Our models are 98-740 × smaller and 3-6% more accurate over the state-of-the-art. We also estimate head pose with absolute errors as low as 5 degrees using 20kB filters, achieving up to 1.6 × precision improvement over existing techniques. Auritus is available at https://github.com/nesl/auritus.","journal":null,"year":2022,"id":314412,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":0.0,"corpus_rank":10062,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.8699,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":842092,"name":"Sandeep Singh Sandha","orcid":"0000-0003-1421-1880","position":1,"is_corresponding":false},{"id":932067,"name":"Siyou Pei","orcid":"0000-0003-3802-8298","position":2,"is_corresponding":false},{"id":932068,"name":"Vivek Jain","orcid":"0000-0002-8666-0784","position":3,"is_corresponding":false},{"id":570142,"name":"Ziqi Wang","orcid":"0000-0002-0232-125X","position":4,"is_corresponding":false},{"id":1013190,"name":"Yuchen Li","orcid":"0000-0002-4740-4171","position":5,"is_corresponding":false},{"id":932070,"name":"Ankur Sarker","orcid":"0000-0003-4232-3345","position":6,"is_corresponding":false},{"id":563489,"name":"Mani Srivastava","orcid":"0000-0002-3782-9192","position":7,"is_corresponding":false},{"id":842091,"name":"Swapnil Sayan Saha","orcid":"0000-0001-5357-2254","position":0,"is_corresponding":true}],"reference_count":1,"raw_metadata":null,"created_at":"2026-07-19T00:33:52.047924Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}