Daniel Steven Rubin, Marcin Straczkiewicz, Emi Yamamoto, Maria Lucia L Madariaga, Mark Ferguson, Jennifer S Brach, Nancy W Glynn, Sang Mee Lee, Margaret Danilovich, Megan Huisingh-Scheetz
{"title":"A Smartphone Application to Measure Walking Cadence before Major Abdominal Surgery in Older Adults.","authors":"Daniel Steven Rubin, Marcin Straczkiewicz, Emi Yamamoto, Maria Lucia L Madariaga, Mark Ferguson, Jennifer S Brach, Nancy W Glynn, Sang Mee Lee, Margaret Danilovich, Megan Huisingh-Scheetz","doi":"10.1159/000545982","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Preoperative physical functional assessments (i.e., assessments that measure capability to perform physical activity) are integral to estimate perioperative risk for older adults. However, these assessments are not routinely performed in-clinic prior to surgery. Walking cadence, or the number of steps walked in a specified amount of time (i.e., steps/min), measures activity intensity and may be able to identify high-risk patients prior to surgery. Smartphones can measure walking characteristics and guide patients through remote functional assessments. Here, we assess feasibility, acceptability, and accuracy of Walk Test, a smartphone application designed to measure walking cadence.</p><p><strong>Methods: </strong>We performed a prospective cohort study of older adults prior to abdominal surgery and enrolled them remotely to perform at-home usual- and fast-paced walks with subsequent validation in-clinic. Each walk (usual- and fast-paced) was 2 min in duration. Feasibility was assessed if 80% of patients could perform all study procedures; acceptability was measured using the Post-Study Survey Usability Questionnaire (PSSUQ); accuracy of our approach was assessed with Lin's concordance coefficient (CCC). activPAL thigh worn accelerometer worn during the in-clinic walk served as a gold standard comparison. We used the CCC to compare the at-home and in-clinic walks as performed by Walk Test.</p><p><strong>Results: </strong>We enrolled 41 participants (mean age 69 ± 5 years, 26 (63%) female); 88% (36/41) successfully completed entire study protocol including independent installation of the application, walk tests (at-home and in-clinic) and questionnaires. Median (interquartile range) overall score of PSSUQ was 1 (1, 1) indicating strong acceptability and usability. The Lin's CCC between the in-clinic activPAL and Walk Test for usual-paced walk was 0.97 (95% CI: 0.96, 0.99, <i>p</i> < 0.001) and for fast-paced walks 0.96 (95% CI: 0.93, 0.98, <i>p</i> < 0.001). The CCC between the at-home and in-clinic walks for usual-paced walks was 0.70 (95% CI: 0.53, 0.86) and for fast-paced walks was 0.46 (95% CI: 0.21, 0.72).</p><p><strong>Conclusion: </strong>We successfully demonstrated the feasibility, acceptability and accuracy of Walk Test to measure walking cadence. Future work is needed to standardize walk test performance at-home to ensure consistency between in-clinic and at-home measures.</p>","PeriodicalId":11242,"journal":{"name":"Digital Biomarkers","volume":"9 1","pages":"113-123"},"PeriodicalIF":0.0000,"publicationDate":"2025-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12240576/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Digital Biomarkers","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1159/000545982","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction: Preoperative physical functional assessments (i.e., assessments that measure capability to perform physical activity) are integral to estimate perioperative risk for older adults. However, these assessments are not routinely performed in-clinic prior to surgery. Walking cadence, or the number of steps walked in a specified amount of time (i.e., steps/min), measures activity intensity and may be able to identify high-risk patients prior to surgery. Smartphones can measure walking characteristics and guide patients through remote functional assessments. Here, we assess feasibility, acceptability, and accuracy of Walk Test, a smartphone application designed to measure walking cadence.
Methods: We performed a prospective cohort study of older adults prior to abdominal surgery and enrolled them remotely to perform at-home usual- and fast-paced walks with subsequent validation in-clinic. Each walk (usual- and fast-paced) was 2 min in duration. Feasibility was assessed if 80% of patients could perform all study procedures; acceptability was measured using the Post-Study Survey Usability Questionnaire (PSSUQ); accuracy of our approach was assessed with Lin's concordance coefficient (CCC). activPAL thigh worn accelerometer worn during the in-clinic walk served as a gold standard comparison. We used the CCC to compare the at-home and in-clinic walks as performed by Walk Test.
Results: We enrolled 41 participants (mean age 69 ± 5 years, 26 (63%) female); 88% (36/41) successfully completed entire study protocol including independent installation of the application, walk tests (at-home and in-clinic) and questionnaires. Median (interquartile range) overall score of PSSUQ was 1 (1, 1) indicating strong acceptability and usability. The Lin's CCC between the in-clinic activPAL and Walk Test for usual-paced walk was 0.97 (95% CI: 0.96, 0.99, p < 0.001) and for fast-paced walks 0.96 (95% CI: 0.93, 0.98, p < 0.001). The CCC between the at-home and in-clinic walks for usual-paced walks was 0.70 (95% CI: 0.53, 0.86) and for fast-paced walks was 0.46 (95% CI: 0.21, 0.72).
Conclusion: We successfully demonstrated the feasibility, acceptability and accuracy of Walk Test to measure walking cadence. Future work is needed to standardize walk test performance at-home to ensure consistency between in-clinic and at-home measures.