{"doi":"10.3390/s24237442","title":"Minimum Electromyography Sensor Set Needed to Identify Age-Related Impairments in the Neuromuscular Control of Walking Using the Dynamic Motor Control Index","abstract":"The dynamic motor control index is an emerging biomarker of age-related neuromuscular impairment. To date, it has been computed by quantifying the co-activity of eleven lower limb muscles. Because clinics that routinely employ electromyography typically collect from fewer muscles, a reduced muscle sensor set may improve the clinical usability of this metric of motor control. This study aimed to test if commonly used eight- and five-muscle electromyography (EMG) sensor sets produce similar dynamic motor control indices as the previously examined eleven-muscle sensor set and similarly differentiate across age subgroups. EMG data were collected during treadmill walking from 36 adults separated into young (N = 18, <35 yrs.), young-old (N = 13, 65–74 yrs.), and old-old (N = 5, ≥75 yrs.) subgroups. Dynamic motor control indices generated using the sensor set with eleven muscles correlated with the eight-muscle set (R2 = 0.70) but not the five-muscle set (R2 = 0.30). Regression models using the eleven-muscle (χ2(4) = 10.62, p = 0.031, Nagelkerke R2 = 0.297) and eight-muscle (χ2(4) = 9.418, p = 0.051, Nagelkerke R2 = 0.267) sets were significant and approaching significance, respectively, whereas the model for the five-muscle set was not significant (p = 0.663, Nagelkerke R2 = 0.073). In both the eleven-muscle (Wald χ2 = 5.16, p = 0.023, OR = 1.26) and eight-muscle models (Wald χ2 = 4.20, p = 0.04, OR = 1.19), a higher index significantly predicted being in the young group compared to the old-old group. Age-related differences in the neuromuscular control of walking can be detected using dynamic motor control indices generated using eleven- and eight-muscle sensor sets, increasing clinical usability of the dynamic motor control index.","journal":"Sensors","year":2024,"id":482319,"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":null,"corpus_rank":null,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9531,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":289294,"name":"Ryan T. Pohlig","orcid":"0000-0002-8385-8218","position":1,"is_corresponding":false},{"id":276919,"name":"Louis N. Awad","orcid":"0000-0002-0159-8011","position":2,"is_corresponding":false},{"id":459770,"name":"Ashley N. Collimore","orcid":"0000-0001-6002-3667","position":0,"is_corresponding":true}],"reference_count":56,"raw_metadata":null,"created_at":"2026-07-19T02:07:14.349221Z","pmid":"39685979","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":[]}