{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T04:45:54Z","timestamp":1791348354088,"version":"4.3.1"},"reference-count":53,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2025,6,20]],"date-time":"2025-06-20T00:00:00Z","timestamp":1750377600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Departmental General Research Fund from the Hong Kong Polytechnic University","award":["P0042679"],"award-info":[{"award-number":["P0042679"]}]},{"name":"Departmental General Research Fund from the Hong Kong Polytechnic University","award":["PolyU 25100122"],"award-info":[{"award-number":["PolyU 25100122"]}]},{"name":"Research Grants Council of the Hong Kong Special Administrative Region","award":["P0042679"],"award-info":[{"award-number":["P0042679"]}]},{"name":"Research Grants Council of the Hong Kong Special Administrative Region","award":["PolyU 25100122"],"award-info":[{"award-number":["PolyU 25100122"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Biosensors"],"abstract":"<jats:p>Smartphone-embedded inertia sensors are widely available nowadays. We have developed a smartphone application that could assess temporal gait characteristics using the built-in inertia measurement unit with the aim of enabling mass screening for gait abnormality. This study aimed to examine the test\u2013retest reliability and concurrent validity of the smartphone-based gait assessment in assessing temporal gait parameters in level-ground walking. Twenty-six healthy young adults (mean age: 20.8 \u00b1 0.7) were recruited. Participants walked at their comfortable pace on a 10 m pathway repetitively in two walking sessions. Gait data were simultaneously collected by the smartphone application and a VICON system during the walk. Gait events of heel strike and toes off were detected from the sensors signal by a peak detection algorithm. Further gait parameters were calculated and compared between the two systems. Pearson Product\u2013Moment Correlation was used to evaluate the concurrent validity of both systems. Test\u2013retest reliability was examined by the intraclass correlation coefficients (ICCs) between measurements from two sessions scheduled one to four weeks apart. The validity of smartphone-based gait assessment was moderate to excellent for parameters involving only heel strike detection (r = 0.628\u20130.977), poor to moderate for parameters involving detection of both heel strike and toes off (r = 0.098\u20130.704), and poor for the proportion of gait phases within a gait cycle. Reliability was good to fair for heel strike-related parameters (ICC = 0.845\u20130.388), good to moderate for heel strike and toes-off-related parameters (ICC = 0.827\u20130.582), and moderate to fair for proportional parameters. Validity was adversely affected when toe off was involved in the calculation, when there was an insufficient number of effective steps taken, or when calculating sub-phases with short duration. The use of smartphone-based gait assessment is recommended in calculating step time and stride time, and we suggest collecting no less than 100 steps per leg during clinical application for better validity and reliability.<\/jats:p>","DOI":"10.3390\/bios15070397","type":"journal-article","created":{"date-parts":[[2025,6,20]],"date-time":"2025-06-20T05:17:42Z","timestamp":1750396662000},"page":"397","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Validity and Reliability of a Smartphone-Based Gait Assessment in Measuring Temporal Gait Parameters: Challenges and Recommendations"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1396-9270","authenticated-orcid":false,"given":"Sam Guoshi","family":"Liang","sequence":"first","affiliation":[{"name":"Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, 11 Yuk Choi Road, Hung Hom, Kowloon City, Hong Kong"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ho Yin","family":"Chung","sequence":"additional","affiliation":[{"name":"Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, 11 Yuk Choi Road, Hung Hom, Kowloon City, Hong Kong"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ka Wing","family":"Chu","sequence":"additional","affiliation":[{"name":"Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, 11 Yuk Choi Road, Hung Hom, Kowloon City, Hong Kong"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuk Hong","family":"Gao","sequence":"additional","affiliation":[{"name":"Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, 11 Yuk Choi Road, Hung Hom, Kowloon City, Hong Kong"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fong Ying","family":"Lau","sequence":"additional","affiliation":[{"name":"Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, 11 Yuk Choi Road, Hung Hom, Kowloon City, Hong Kong"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wolfe Ixin","family":"Lai","sequence":"additional","affiliation":[{"name":"Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, 11 Yuk Choi Road, Hung Hom, Kowloon City, Hong Kong"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7253-5288","authenticated-orcid":false,"given":"Gabriel Ching-Hang","family":"Fong","sequence":"additional","affiliation":[{"name":"Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, 11 Yuk Choi Road, Hung Hom, Kowloon City, Hong Kong"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1834-5715","authenticated-orcid":false,"given":"Patrick Wai-Hang","family":"Kwong","sequence":"additional","affiliation":[{"name":"Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, 11 Yuk Choi Road, Hung Hom, Kowloon City, Hong Kong"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9918-541X","authenticated-orcid":false,"given":"Freddy Man Hin","family":"Lam","sequence":"additional","affiliation":[{"name":"Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, 11 Yuk Choi Road, Hung Hom, Kowloon City, Hong Kong"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,6,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Clark, D.J. (2015). Automaticity of walking: Functional significance, mechanisms, measurement and rehabilitation strategies. Front. Hum. Neurosci., 9.","DOI":"10.3389\/fnhum.2015.00246"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1310\/tsr1501-51","article-title":"Functional capacity and health-related quality of life in individuals post stroke","volume":"15","author":"Muren","year":"2008","journal-title":"Top. Stroke Rehabil."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"2367","DOI":"10.1007\/s00701-022-05309-4","article-title":"Gait, falls, cognitive function, and health-related quality of life after shunt-treated idiopathic normal pressure hydrocephalus\u2014A single-center study","volume":"164","author":"Hallqvist","year":"2022","journal-title":"Acta Neurochir."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"369","DOI":"10.1016\/0167-9457(96)00006-1","article-title":"Clinical gait analysis: A review","volume":"15","author":"Whittle","year":"1996","journal-title":"Hum. Mov. Sci."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/j.gaitpost.2011.03.027","article-title":"Efficacy of clinical gait analysis: A systematic review","volume":"34","author":"Wren","year":"2011","journal-title":"Gait Posture"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1109\/RBME.2018.2807182","article-title":"A Review on Accelerometry-Based Gait Analysis and Emerging Clinical Applications","volume":"11","author":"Jarchi","year":"2018","journal-title":"IEEE Rev. Biomed. Eng."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1109\/JBHI.2021.3092875","article-title":"Human Gait Analysis in Neurodegenerative Diseases: A Review","volume":"26","author":"Cicirelli","year":"2022","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Faccioli, S., Cavalagli, A., Falocci, N., Mangano, G., Sanfilippo, I., and Sassi, S. (2023). Gait analysis patterns and rehabilitative interventions to improve gait in persons with hereditary spastic paraplegia: A systematic review and meta-analysis. Front. Neurol., 14.","DOI":"10.3389\/fneur.2023.1256392"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Byun, S., Han, J.W., Kim, T.H., and Kim, K.W. (2016). Test-Retest Reliability and Concurrent Validity of a Single Tri-Axial Accelerometer-Based Gait Analysis in Older Adults with Normal Cognition. PLoS ONE, 11.","DOI":"10.1371\/journal.pone.0158956"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"929","DOI":"10.1093\/gerona\/gls256","article-title":"Assessing the Temporal Relationship Between Cognition and Gait: Slow Gait Predicts Cognitive Decline in the Mayo Clinic Study of Aging","volume":"68","author":"Mielke","year":"2013","journal-title":"J. Gerontol. Ser. A"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Chen, X., Liao, S., Cao, S., Wu, D., and Zhang, X. (2017). An Acceleration-Based Gait Assessment Method for Children with Cerebral Palsy. Sensors, 17.","DOI":"10.3390\/s17051002"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1016\/j.gaitpost.2020.05.031","article-title":"Clinical efficacy of instrumented gait analysis: Systematic review 2020 update","volume":"80","author":"Wren","year":"2020","journal-title":"Gait Posture"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"608","DOI":"10.1093\/gerona\/glu225","article-title":"Ambulatory Fall-Risk Assessment: Amount and Quality of Daily-Life Gait Predict Falls in Older Adults","volume":"70","author":"Pijnappels","year":"2015","journal-title":"J. Gerontol. Ser. A"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"afac205","DOI":"10.1093\/ageing\/afac205","article-title":"World guidelines for falls prevention and management for older adults: A global initiative","volume":"51","author":"Martin","year":"2022","journal-title":"Age Ageing"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"809","DOI":"10.2522\/ptj.20120163","article-title":"Assessing the Validity of the Dynamic Gait Index in a Balance Disorders Clinic: An Application of Rasch Analysis","volume":"93","author":"Dye","year":"2013","journal-title":"Phys. Ther."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Zhao, Y., Yu, L., Fan, X., Pang, M.Y.C., Tsui, K.-L., and Wang, H. (2023). Design of a Sensor-Technology-Augmented Gait and Balance Monitoring System for Community-Dwelling Older Adults in Hong Kong: A Pilot Feasibility Study. Sensors, 23.","DOI":"10.3390\/s23188008"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1016\/j.cmpb.2012.02.003","article-title":"Estimation of spatial-temporal gait parameters in level walking based on a single accelerometer: Validation on normal subjects by standard gait analysis","volume":"108","author":"Benedetti","year":"2012","journal-title":"Comput. Methods Programs Biomed."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"17505","DOI":"10.1109\/JSEN.2021.3050175","article-title":"Soft Wrist-Worn Multi-Functional Sensor Array for Real-Time Hand Gesture Recognition","volume":"22","author":"Dong","year":"2022","journal-title":"IEEE Sens. J."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Prieto-Avalos, G., Cruz-Ramos, N.A., Alor-Hern\u00e1ndez, G., S\u00e1nchez-Cervantes, J.L., Rodr\u00edguez-Mazahua, L., and Guarneros-Nolasco, L.R. (2022). Wearable Devices for Physical Monitoring of Heart: A Review. Biosensors, 12.","DOI":"10.3390\/bios12050292"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1146\/annurev-med-052422-020437","article-title":"Wearable Devices: Implications for Precision Medicine and the Future of Health Care","volume":"75","author":"Babu","year":"2024","journal-title":"Annu. Rev. Med."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1521","DOI":"10.1109\/JBHI.2016.2608720","article-title":"Toward Pervasive Gait Analysis with Wearable Sensors: A Systematic Review","volume":"20","author":"Chen","year":"2016","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"872","DOI":"10.5535\/arm.2018.42.6.872","article-title":"Evaluation of Validity and Reliability of Inertial Measurement Unit-Based Gait Analysis Systems","volume":"42","author":"Cho","year":"2018","journal-title":"Ann. Rehabil. Med."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"686","DOI":"10.1177\/09544119211072971","article-title":"Validation of wearable inertial sensor-based gait analysis system for measurement of spatiotemporal parameters and lower extremity joint kinematics in sagittal plane","volume":"236","author":"Patel","year":"2022","journal-title":"Proc. Inst. Mech. Eng. Part H J. Eng. Med."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1016\/j.gaitpost.2023.12.015","article-title":"Gait kinematics based on inertial measurement units with the sensor-to-segment calibration and multibody optimization adapted to the patient\u2019s motor capacities, a pilot study","volume":"108","author":"Pacher","year":"2024","journal-title":"Gait Posture"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"212","DOI":"10.1016\/j.gaitpost.2023.10.006","article-title":"Inertial measurement unit sensor-based gait analysis in adults and older adults: A cross-sectional study","volume":"107","author":"Yoon","year":"2024","journal-title":"Gait Posture"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Arshad, M.Z., Jamsrandorj, A., Kim, J., and Mun, K.-R. (2022). Gait Events Prediction Using Hybrid CNN-RNN-Based Deep Learning Models through a Single Waist-Worn Wearable Sensor. Sensors, 22.","DOI":"10.3390\/s22218226"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"322","DOI":"10.1016\/j.gaitpost.2009.11.014","article-title":"Real-time gait event detection for normal subjects from lower trunk accelerations","volume":"31","author":"Alvarez","year":"2010","journal-title":"Gait Posture"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1935","DOI":"10.1007\/s10439-014-1232-0","article-title":"Validity and Reliability of Gait and Postural Control Analysis Using the Tri-axial Accelerometer of the iPod Touch","volume":"43","author":"Kosse","year":"2015","journal-title":"Ann. Biomed. Eng."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"516","DOI":"10.1016\/j.gaitpost.2017.09.030","article-title":"Reliability and validity of a smartphone-based assessment of gait parameters across walking speed and smartphone locations: Body, bag, belt, hand, and pocket","volume":"58","author":"Silsupadol","year":"2017","journal-title":"Gait Posture"},{"key":"ref_30","unstructured":"Kirk, C., Kuderle, A., Mico-Amigo, M.E., Bonci, T., Paraschiv-Ionescu, A., Ullrich, M., Soltani, A., Gazit, E., Salis, F., and Alcock, L. (2024). Mobilise-D insights to estimate real-world walking speed in multiple conditions with a wearable device. Sci. Rep., 14."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Brognara, L. (2024). Gait Assessment Using Smartphone Applications in Older Adults: A Scoping Review. Geriatrics, 9.","DOI":"10.3390\/geriatrics9040095"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"van Schooten, K.S., Pijnappels, M., Rispens, S.M., Elders, P.J., Lips, P., Daffertshofer, A., Beek, P.J., and van Dieen, J.H. (2016). Daily-Life Gait Quality as Predictor of Falls in Older People: A 1-Year Prospective Cohort Study. PLoS ONE, 11.","DOI":"10.1371\/journal.pone.0158623"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Mohammed, Z., Elfadel, I.M., and Rasras, M. (2018). Monolithic Multi Degree of Freedom (MDoF) Capacitive MEMS Accelerometers. Micromachines, 9.","DOI":"10.3390\/mi9110602"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Grouios, G., Ziagkas, E., Loukovitis, A., Chatzinikolaou, K., and Koidou, E. (2023). Accelerometers in Our Pocket: Does Smartphone Accelerometer Technology Provide Accurate Data?. Sensors, 23.","DOI":"10.3390\/s23010192"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1016\/S0966-6362(97)00021-0","article-title":"Displacement of the pelvis during human walking: Experimental data and model predictions","volume":"6","author":"Zijlstra","year":"1997","journal-title":"Gait Posture"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Rantalainen, T., Karavirta, L., Pirkola, H., Rantanen, T., and Linnamo, V. (2020). Gait Variability Using Waist- and Ankle-Worn Inertial Measurement Units in Healthy Older Adults. Sensors, 20.","DOI":"10.3390\/s20102858"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"20552076241257054","DOI":"10.1177\/20552076241257054","article-title":"Validation of gait analysis using smartphones: Reliability and validity","volume":"10","author":"Tao","year":"2024","journal-title":"Digit. Health"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1186\/s13018-022-03300-4","article-title":"The validity and reliability of the OneStep smartphone application under various gait conditions in healthy adults with feasibility in clinical practice","volume":"17","author":"Christensen","year":"2022","journal-title":"J. Orthop. Surg. Res."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Marom, P., Brik, M., Agay, N., Dankner, R., Katzir, Z., Keshet, N., and Doron, D. (2024). The Reliability and Validity of the OneStep Smartphone Application for Gait Analysis among Patients Undergoing Rehabilitation for Unilateral Lower Limb Disability. Sensors, 24.","DOI":"10.3390\/s24113594"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1815","DOI":"10.1111\/j.1460-9568.2006.05033.x","article-title":"Marked alterations in the gait timing and rhythmicity of patients with de novo Parkinson\u2019s disease","volume":"24","author":"Baltadjieva","year":"2006","journal-title":"Eur. J. Neurosci."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1287","DOI":"10.1017\/S1041610218001783","article-title":"Gait parameters and characteristics associated with increased risk of falls in people with dementia: A systematic review","volume":"31","author":"Modarresi","year":"2019","journal-title":"Int. Psychogeriatr."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Springer, S., and Yogev Seligmann, G. (2016). Validity of the Kinect for Gait Assessment: A Focused Review. Sensors, 16.","DOI":"10.3390\/s16020194"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Albert, J.A., Owolabi, V., Gebel, A., Brahms, C.M., Granacher, U., and Arnrich, B. (2020). Evaluation of the Pose Tracking Performance of the Azure Kinect and Kinect v2 for Gait Analysis in Comparison with a Gold Standard: A Pilot Study. Sensors, 20.","DOI":"10.3390\/s20185104"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Hockett, S., Dunbar, S., Williams, C., Sturdivant, R., Garner, B., and Rylander, J. (2024). Comparison of spatiotemporal gait parameter measurements across various emulated foot strike patterns between the Tekscan\u00ae Strideway\u2122 pressure sensitive walkway and gold-standard marker-based motion capture. J. Biomech., 176.","DOI":"10.1016\/j.jbiomech.2024.112310"},{"key":"ref_45","unstructured":"Vicon (2024, February 10). Plug-in Gait Reference Guide. Available online: https:\/\/help.vicon.com\/space\/Nexus216\/11607059\/Plug-in+Gait+Reference+Guide#Plug-inGaitReferenceGuide."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"933","DOI":"10.1109\/TBME.2015.2480296","article-title":"Step Detection and Parameterization for Gait Assessment Using a Single Waist-Worn Accelerometer","volume":"63","author":"Soaz","year":"2016","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"400","DOI":"10.1016\/j.medengphy.2015.02.003","article-title":"Instrumenting gait with an accelerometer: A system and algorithm examination","volume":"37","author":"Godfrey","year":"2015","journal-title":"Med. Eng. Phys."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Mikkonen, J., Leinonen, V., Luomajoki, H., Kaski, D., Kupari, S., Tarvainen, M., Selander, T., and Airaksinen, O. (2021). Cross-Cultural Adaptation, Reliability, and Psychophysical Validation of the Pain and Sleep Questionnaire Three-Item Index in Finnish. J. Clin. Med., 10.","DOI":"10.3390\/jcm10214887"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"141","DOI":"10.11613\/BM.2015.015","article-title":"Understanding Bland Altman analysis","volume":"25","author":"Giavarina","year":"2015","journal-title":"Biochem. Med."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/j.jcm.2016.02.012","article-title":"A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research","volume":"15","author":"Koo","year":"2016","journal-title":"J. Chiropr. Med."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"89","DOI":"10.12997\/jla.2023.12.2.89","article-title":"Are Only p-Values Less Than 0.05 Significant? A p-Value Greater Than 0.05 Is Also Significant!","volume":"12","author":"Kwak","year":"2023","journal-title":"J. Lipid Atheroscler."},{"key":"ref_52","first-page":"295","article-title":"Concurrent Validity of a Commercial Wireless Trunk Triaxial Accelerometer System for Gait Analysis","volume":"28","author":"Lebleu","year":"2019","journal-title":"J. Sport Rehabil."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1007\/s10916-021-01760-5","article-title":"Gait and Balance Assessments using Smartphone Applications in Parkinson\u2019s Disease: A Systematic Review","volume":"45","author":"Abou","year":"2021","journal-title":"J. Med. 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