Published on 25.04.18 in Vol 5, No 1 (2018): Jan-Jun
Works citing "A Kinematic Sensor and Algorithm to Detect Motor Fluctuations in Parkinson Disease: Validation Study Under Real Conditions of Use"
According to Crossref, the following articles are citing this article (DOI 10.2196/rehab.8335):
(note that this is only a small subset of citations)
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Thorp JE, Adamczyk PG, Ploeg H, Pickett KA. Monitoring Motor Symptoms During Activities of Daily Living in Individuals With Parkinson's Disease. Frontiers in Neurology 2018;9
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Teshuva I, Hillel I, Gazit E, Giladi N, Mirelman A, Hausdorff JM. Using wearables to assess bradykinesia and rigidity in patients with Parkinson’s disease: a focused, narrative review of the literature. Journal of Neural Transmission 2019;126(6):699
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Habets J, Heijmans M, Herff C, Simons C, Leentjens AF, Temel Y, Kuijf M, Kubben P. Mobile Health Daily Life Monitoring for Parkinson Disease: Development and Validation of Ecological Momentary Assessments. JMIR mHealth and uHealth 2020;8(5):e15628
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Evers LJ, Raykov YP, Krijthe JH, Silva de Lima AL, Badawy R, Claes K, Heskes TM, Little MA, Meinders MJ, Bloem BR. Real-Life Gait Performance as a Digital Biomarker for Motor Fluctuations: The Parkinson@Home Validation Study. Journal of Medical Internet Research 2020;22(10):e19068
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Rodríguez-Molinero A, Pérez-López C, Samà A, Rodríguez-Martín D, Alcaine S, Mestre B, Quispe P, Giuliani B, Vainstein G, Browne P, Sweeney D, Quinlan LR, Arostegui JMM, Bayes , Lewy H, Costa A, Annicchiarico R, Counihan T, Laighin G, Cabestany J. Estimating dyskinesia severity in Parkinson’s disease by using a waist-worn sensor: concurrent validity study. Scientific Reports 2019;9(1)
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Morgan C, Rolinski M, McNaney R, Jones B, Rochester L, Maetzler W, Craddock I, Whone AL. Systematic Review Looking at the Use of Technology to Measure Free-Living Symptom and Activity Outcomes in Parkinson’s Disease in the Home or a Home-like Environment. Journal of Parkinson's Disease 2020;10(2):429
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Hørmann Thomsen T, Kjær TW, Bastrup Jørgensen L, Haahr A, Winge K. “Does the Response to Morning Medication Predict the ADL-Level of the Day in Parkinson’s Disease?”. Parkinson's Disease 2020;2020:1
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Gurchiek RD, Choquette RH, Beynnon BD, Slauterbeck JR, Tourville TW, Toth MJ, McGinnis RS. Open-Source Remote Gait Analysis: A Post-Surgery Patient Monitoring Application. Scientific Reports 2019;9(1)
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. Parkinson Disease. CONTINUUM: Lifelong Learning in Neurology 2019;25(4):896
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Del Din S, Kirk C, Yarnall AJ, Rochester L, Hausdorff JM, Mirelman A, Dorsey ER, Brundin P, Bloem BR. Body-Worn Sensors for Remote Monitoring of Parkinson’s Disease Motor Symptoms: Vision, State of the Art, and Challenges Ahead. Journal of Parkinson's Disease 2021;11(s1):S35
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Habets JGV, Heijmans M, Leentjens AFG, Simons CJP, Temel Y, Kuijf ML, Kubben PL, Herff C. A Long-Term, Real-Life Parkinson Monitoring Database Combining Unscripted Objective and Subjective Recordings. Data 2021;6(2):22
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Heidarivincheh F, McConville R, Morgan C, McNaney R, Masullo A, Mirmehdi M, Whone AL, Craddock I. Multimodal Classification of Parkinson’s Disease in Home Environments with Resiliency to Missing Modalities. Sensors 2021;21(12):4133
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Barrachina-Fernández M, Maitín AM, Sánchez-Ávila C, Romero JP. Wearable Technology to Detect Motor Fluctuations in Parkinson’s Disease Patients: Current State and Challenges. Sensors 2021;21(12):4188
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Milano F, Cerro G, Santoni F, De Angelis A, Miele G, Rodio A, Moschitta A, Ferrigno L, Carbone P. Parkinson’s Disease Patient Monitoring: A Real-Time Tracking and Tremor Detection System Based on Magnetic Measurements. Sensors 2021;21(12):4196
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Perrote F, Zeppa G, Coca H, Figueroa S, de Battista JC. Evaluación de un sistema de sensores inerciales externos tipo Holter en pacientes con enfermedad de Parkinson en Argentina. Neurología Argentina 2021;13(3):153
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Sotirakis C, Conway N, Su Z, Villarroel M, Tarassenko L, FitzGerald JJ, Antoniades CA. Longitudinal Monitoring of Progressive Supranuclear Palsy using Body‐Worn Movement Sensors. Movement Disorders 2022;37(11):2263
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Thomsen TH, Jørgensen LB, Kjær TW, Haahr A, Vogel A, Larsen IU, Winge K. Clinical Markers of 6 Pre-dominant Coping Behaviors in Living With Parkinson Disease: A Convergent Mixed Methods Study. INQUIRY: The Journal of Health Care Organization, Provision, and Financing 2022;59:004695802211299
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Pierleoni P, Raggiunto S, Belli A, Paniccia M, Bazgir O, Palma L. A Single Wearable Sensor for Gait Analysis in Parkinson’s Disease: A Preliminary Study. Applied Sciences 2022;12(11):5486
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Kenny L, Moore K, O' Riordan C, Fox S, Barton J, Tedesco S, Sica M, Crowe C, Alamäki A, Condell J, Nordström A, Timmons S. The Views and Needs of People With Parkinson Disease Regarding Wearable Devices for Disease Monitoring: Mixed Methods Exploration. JMIR Formative Research 2022;6(1):e27418
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Soundararajan R, Prabu AV, Routray S, Malla PP, Ray AK, Palai G, Faragallah OS, Baz M, Abualnaja MM, Eid MMA, Rashed ANZ. Deeply Trained Real-Time Body Sensor Networks for Analyzing the Symptoms of Parkinson’s Disease. IEEE Access 2022;10:63403
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Pérez-López C, Hernández-Vara J, Caballol N, Bayes , Buongiorno M, Lopez-Ariztegui N, Gironell A, López-Sánchez J, Martínez-Castrillo JC, Sauco M A, López-Manzanares L, Escalante-Arroyo S, Pérez-Martínez DA, Rodríguez-Molinero A. Comparison of the Results of a Parkinson's Holter Monitor With Patient Diaries, in Real Conditions of Use: A Sub-analysis of the MoMoPa-EC Clinical Trial. Frontiers in Neurology 2022;13
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Rodríguez-Martín D, Cabestany J, Pérez-López C, Pie M, Calvet J, Samà A, Capra C, Català A, Rodríguez-Molinero A. A New Paradigm in Parkinson's Disease Evaluation With Wearable Medical Devices: A Review of STAT-ONTM. Frontiers in Neurology 2022;13
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Rodríguez-Molinero A, Hernández-Vara J, Miñarro A, Pérez-López C, Bayes-Rusiñol , Martínez-Castrillo JC, Pérez-Martínez DA. Multicentre, randomised, single-blind, parallel group trial to compare
the effectiveness of a Holter for Parkinson’s symptoms against other
clinical monitoring methods: study protocol. BMJ Open 2021;11(7):e045272
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Guerra A, D’Onofrio V, Ferreri F, Bologna M, Antonini A. Objective measurement versus clinician-based assessment for Parkinson’s disease. Expert Review of Neurotherapeutics 2023;23(8):689
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de Villers-Sidani , Voss P, Guitton D, Cisneros-Franco JM, Koch NA, Ducharme S. A novel tablet-based software for the acquisition and analysis of gaze and eye movement parameters: a preliminary validation study in Parkinson’s disease. Frontiers in Neurology 2023;14
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Löhle M, Timpka J, Bremer A, Khodakarami H, Gandor F, Horne M, Ebersbach G, Odin P, Storch A. Application of single wrist-wearable accelerometry for objective motor diary assessment in fluctuating Parkinson’s disease. npj Digital Medicine 2023;6(1)
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Sotirakis C, Su Z, Brzezicki MA, Conway N, Tarassenko L, FitzGerald JJ, Antoniades CA. Identification of motor progression in Parkinson’s disease using wearable sensors and machine learning. npj Parkinson's Disease 2023;9(1)
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Fietzek UM, Messner M, Levin J. Kann KI Parkinson?. Nervenheilkunde 2023;42(09):612
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Feldmann LK, Roudini J, Kühn AA, Habets JGV. Improving naturalistic neuroscience with patient engagement strategies. Frontiers in Human Neuroscience 2024;17
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According to Crossref, the following books are citing this article (DOI 10.2196/rehab.8335):
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Harte R, Ó Laighin G, Quinlan L. Digital Health. 2021. :101
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Bianchini E, Maetzler W. Digital Technologies in Movement Disorders. 2023. :93
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. Handbook of Digital Technologies in Movement Disorders. 2024. :129
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Tönges L, Deuschl G. Handbook of Digital Technologies in Movement Disorders. 2024. :27
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