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PARKİNSONDA TEKNOLOJİK TABANLI DEĞERLENDİRME

Yıl 2024, Cilt: 46 Sayı: 3, 156 - 163, 30.09.2024
https://doi.org/10.7197/cmj.1512299

Öz

Parkinson hastalığı, motor ve motor olmayan semptomlarla karakterize nörodejeneratif bir hastalıktır ve bu semptomlar zaman içinde kötüleşir. Günümüzde hastalığın ilerleyişini izlemek ve tedavi yanıtlarını değerlendirmek için geleneksel klinik değerlendirme yöntemleri kullanılmaktadır. Ancak bu yöntemler subjektiftir ve belirli durumları ölçmede yetersiz kalabilir. Son yıllarda, giyilebilir teknolojiler, akıllı sensörler ve veri analizindeki ilerlemeler sayesinde parkinson hastalarının değerlendirilmesinde teknolojik tabanlı yaklaşımlar daha fazla dikkat çekmektedir. Bu teknolojiler sayesinde hastaların günlük aktiviteleri, motor fonksiyonları ve semptomları izlenilerek objektif veriler elde edilebilir. Tremor şiddeti, rijidite, bradikinezi, postüral instabiliteler, donma fenomeni ve konuşma bozukluğunun motor parametreleri gibi motor semptomlar bu teknolojiler aracılığıyla objektif olarak ölçülebilir. Ayrıca, bu verilerin uzaktan aktarılabilmesi, hastaların kendi evlerinde değerlendirilebilmesine olanak tanır ve sağlık uzmanlarına sürekli geri bildirim sağlar. Bu derleme, parkinson hastalarında teknolojik tabanlı değerlendirme yöntemlerinin önemini ve potansiyelini vurgulamakta ve gelecekteki araştırmalara rehberlik etmeyi amaçlamaktadır.

Kaynakça

  • 1. Fahn S. Unified Parkinson's disease rating scale. Recent developments in Parkinson's disease. 1987:153-63.
  • 2. Balestrino R, Schapira A. Parkinson disease. European journal of neurology. 2020;27(1):27-42. doi: 10.1111/ene.14108.
  • 3. Güler, S., Caylan, A., Turan, F. N., & Dağdeviren, N. (2022). Prevalence and Clinical Features of Idiopathic Parkinson’s Disease in Western Turkey. Archives of Neuropsychiatry, 59(2), 98. doi: 10.29399/npa.27486.
  • 4. Pringsheim T, Jette N, Frolkis A, Steeves TD. The prevalence of Parkinson's disease: a systematic review and meta‐analysis. Movement disorders. 2014;29(13):1583-90. doi: 10.1002/ mds.25945.
  • 5. Dorsey ER, Bloem BR. The Parkinson pandemic—a call to action. JAMA neurology. 2018;75(1):9-10. doi: 10.1001/ jamaneurol.2017.3299.
  • 6. Dorsey ER, Elbaz A, Nichols E, Abbasi N, Abd-Allah F, Abdelalim A, et al. Global, regional, and national burden of Parkinson's disease, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. The Lancet Neurology. 2018;17(11):939-53. doi: 10.1016/S1474-4422(18)30295-3.
  • 7. Jankovic J, Tan EK. Parkinson’s disease: etiopathogenesis and treatment. Journal of Neurology, Neurosurgery & Psychiatry. 2020;91(8):795-808. doi: 10.1136/jnnp-2019-322338.
  • 8. Wolters EC. Variability in the clinical expression of Parkinson's disease. Journal of the neurological sciences. 2008;266(1-2):197-203. doi: 10.1016/j.jns.2007.08.016.
  • 9. Hoehn MM. Commentary: Parkinsonism: Onset, progression, and mortality. Neurology. 1998;50:318-. doi: 10.1212/wnl. 50.2.318.
  • 10. Ozanne A, Johansson D, Hällgren Graneheim U, Malmgren K, Bergquist F, Alt Murphy M. Wearables in epilepsy and Parkinson's disease—a focus group study. Acta Neurologica Scandinavica. 2018;137(2):188-94. doi: 10.1111/ane.12798.
  • 11. Qu Y, Zhang T, Duo Y, Chen L, Li X. Identification and quantitative assessment of motor complications in Parkinson’s disease using the Parkinson’s KinetiGraph™. Frontiers in Aging Neuroscience. 2023;15. doi: 10.3389/fnagi.2023.1142268.
  • 12. Espay AJ, Bonato P, Nahab FB, Maetzler W, Dean JM, Klucken J, et al. Technology in Parkinson's disease: challenges and opportunities. Movement Disorders. 2016;31(9):1272-82. doi: 10.1002/mds.26642.
  • 13. Rovini E, Maremmani C, Cavallo F. How wearable sensors can support Parkinson's disease diagnosis and treatment: a systematic review. Frontiers in neuroscience. 2017;11:555. doi: 10.3389/fnins.2017.00555.
  • 14. Di Lazzaro G, Ricci M, Al-Wardat M, Schirinzi T, Scalise S, Giannini F, et al. Technology-based objective measures detect subclinical axial signs in untreated, de novo Parkinson’s disease. Journal of Parkinson's disease. 2020;10(1):113-22. doi: 10.3233/JPD-191758
  • 15. Godinho C, Domingos J, Cunha G, Santos AT, Fernandes RM, Abreu D, et al. A systematic review of the characteristics and validity of monitoring technologies to assess Parkinson’s disease. Journal of neuroengineering and rehabilitation. 2016;13:1-10. doi: 10.1186/s12984-016-0136-7.
  • 16. Özen D, Karakaya MG, Yenişehir S, Çıtak İ. Parkinsonlu Hastalarda Teknoloji Temelli Yürüyüş Değerlendirmelerinin Literatür Analizi Literature Analysis Of Technology-Based Gait Assessment In Patients With Parkinson Disease. Full Text Book.56.
  • 17. Moreau C, Rouaud T, Grabli D, Benatru I, Remy P, Marques A-R, et al. Overview on wearable sensors for the management of Parkinson’s disease. NPJ Parkinson's Disease. 2023;9(1):153. doi: 10.1038/s41531-023-00585-y.
  • 18. Suppa A, Kita A, Leodori G, Zampogna A, Nicolini E, Lorenzi P, et al. L-DOPA and freezing of gait in Parkinson’s disease: Objective assessment through a wearable wireless system. Frontiers in neurology. 2017;8:406. doi: 10.3389/fneur. 2017.00406.
  • 19. Bove F, Di Lazzaro G, Mulas D, Cocciolillo F, Di Giuda D, Bentivoglio AR. A role for accelerometry in the differential diagnosis of tremor syndromes. Functional neurology. 2018;33(1):45. doi: 10.11138/fneur/2018.33.1.045
  • 20. Delrobaei M, Tran S, Gilmore G, McIsaac K, Jog M. Characterization of multi-joint upper limb movements in a single task to assess bradykinesia. Journal of the neurological sciences. 2016;368:337-42. doi: 10.1016/j.jns.2016.07.056.
  • 21. Ricci M, Giannini F, Saggio G, Cenci C, Di Lazzaro G, Pisani A, editors. A novel analytical approach to assess dyskinesia in patients with Parkinson disease. 2018 IEEE international symposium on medical measurements and applications (MeMeA). 2018; (pp. 1-5), IEEE. doi: 10.1109/MeMeA.2018.8438666.
  • 22. Kaya D, Soyukibar TE. Parkinson’s Disease and Parkinsonism. The Journal of Turkish Family Physician. 2022;13(4):182-92. doi: 10.15511/tjtfp.22.00482
  • 23. Jankovic J. Parkinson’s disease: clinical features and diagnosis. Journal of neurology, neurosurgery & psychiatry. 2008;79(4):368-76. doi: 10.1136/jnnp.2007.131045.
  • 24. Kraus P, Lemke M, Reichmann H. Kinetic tremor in Parkinson’s disease–an underrated symptom. Journal of neural transmission. 2006;113:845-53. doi: 10.1007/s00702-005-0354-9.
  • 25. Fleischman DA, Wilson RS, Schneider JA, Bienias JL, Bennett DA. Parkinsonian signs and functional disability in old age. Experimental aging research. 2007;33(1):59-76. doi: 10.1080/03610730601006370.
  • 26. Rigas G, Tzallas AT, Tsipouras MG, Bougia P, Tripoliti EE, Baga D, et al. Assessment of tremor activity in the Parkinson’s disease using a set of wearable sensors. IEEE Transactions on Information Technology in Biomedicine. 2012;16(3):478-87. doi: 10.1109/TITB.2011.2182616.
  • 27. Heldman DA, Jankovic J, Vaillancourt DE, Prodoehl J, Elble RJ, Giuffrida JP. Essential tremor quantification during activities of daily living. Parkinsonism & related disorders. 2011;17(7):537-42. doi: 10.1016/j.parkreldis.2011.04.017.
  • 28. Delrobaei M, Memar S, Pieterman M, Stratton TW, McIsaac K, Jog M. Towards remote monitoring of Parkinson’s disease tremor using wearable motion capture systems. Journal of the neurological sciences. 2018;384:38-45. doi: 10.1016/ j.jns.2017.11.004.
  • 29. Grimaldi G, Manto M-U, Manto M. Tremor: from pathogenesis to treatment: Morgan & Claypool Publishers; 2008.
  • 30. Rahimi F, Bee C, South A, Debicki D, Jog M, editors. Variability of hand tremor in rest and in posture—A pilot study. In 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society; 2011: IEEE. doi: 10.1109/IEMBS.2011.6090067.
  • 31. Braybrook M, O’Connor S, Churchward P, Perera T, Farzanehfar P, Horne M. An ambulatory tremor score for Parkinson’s disease. Journal of Parkinson's disease. 2016;6(4):723-31. doi: 10.3233/JPD-160898.
  • 32. Wile DJ, Ranawaya R, Kiss ZH. Smart watch accelerometry for analysis and diagnosis of tremor. Journal of neuroscience methods. 2014;230:1-4. doi: 10.1016/j.jneumeth.2014.04. 021.
  • 33. Salarian A, Russmann H, Wider C, Burkhard PR, Vingerhoets FJ, Aminian K. Quantification of tremor and bradykinesia in Parkinson's disease using a novel ambulatory monitoring system. IEEE Transactions on biomedical engineering. 2007;54(2):313-22. doi: 10.1109/TBME.2006.886670
  • 34. Tysnes O-B, Storstein A. Epidemiology of Parkinson’s disease. Journal of neural transmission. 2017;124:901-5. doi: 10.1007/s00702-017-1686-y.
  • 35. 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;126:699-710. doi: 10.1007/s00702-019-02017-9.
  • 36. Ferreira-Sánchez MdR, Moreno-Verdú M, Cano-de-La-Cuerda R. Quantitative measurement of rigidity in Parkinson’s disease: a systematic review. Sensors. 2020;20(3):880. doi: 10.3390/s20030880.
  • 37. Gao J, He W, Du L-J, Li S, Cheng L-G, Shih G, et al. Ultrasound strain elastography in assessment of resting biceps brachii muscle stiffness in patients with Parkinson's disease: a primary observation. Clinical Imaging. 2016;40(3):440-4. doi: 10.1016/j.clinimag.2015.12.008.
  • 38. López-de-Celis C, Pérez-Bellmunt A, Bueno-Gracia E, Fanlo-Mazas P, Zárate-Tejero CA, Llurda-Almuzara L, et al. Effect of diacutaneous fibrolysis on the muscular properties of gastrocnemius muscle. PLoS One. 2020;15(12):e0243225. doi: 10.1371/journal.pone.0243225.
  • 39. Kisilewicz A, Madeleine P, Ignasiak Z, Ciszek B, Kawczynski A, Larsen RG. Eccentric exercise reduces upper trapezius muscle stiffness assessed by shear wave elastography and myotonometry. Frontiers in Bioengineering and Biotechnology. 2020;8:928. doi: 10.3389/fbioe.2020.00928.
  • 40. Agyapong-Badu S, Warner M, Samuel D, Stokes M. Practical considerations for standardized recording of muscle mechanical properties using a myometric device: Recording site, muscle length, state of contraction and prior activity. Journal of Musculoskeletal Research. 2018;21(02):1850010. doi: 10.1142/S0218957718500100.
  • 41. Rätsep T, Asser T. Changes in viscoelastic properties of skeletal muscles induced by subthalamic stimulation in patients with Parkinson's disease. Clinical biomechanics. 2011;26(2):213-7. doi: 10.1016/j.clinbiomech.2010.09.014.
  • 42. Gäverth J, Sandgren M, Lindberg PG, Forssberg H, Eliasson A-C. Test-retest and inter-rater reliability of a method to measure wrist and finger spasticity. Journal of rehabilitation medicine. 2013;45(7):630-6. doi: 10.2340/16501977-1160.
  • 43. Zetterberg H, Frykberg GE, Gäverth J, Lindberg P. Neural and nonneural contributions to wrist rigidity in Parkinson’s disease: an explorative study using the NeuroFlexor. BioMed research international. 2015;2015. doi: 10.1155/2015/ 276182.
  • 44. Perera T, Lee W-L, Jones M, Tan JL, Proud EL, Begg A, et al. A palm-worn device to quantify rigidity in Parkinson’s disease. Journal of neuroscience methods. 2019;317:113-20. doi: 10.1016/j.jneumeth.2019.02.006.
  • 45. Reichmann H. Clinical criteria for the diagnosis of Parkinson’s disease. Neurodegenerative diseases. 2010;7(5):284-90. doi: 10.1159/000314478.
  • 46. Lee WL, Sinclair NC, Jones M, Tan JL, Proud EL, Peppard R, et al. Objective evaluation of bradykinesia in Parkinson’s disease using an inexpensive marker-less motion tracking system. Physiological measurement. 2019;40(1):014004. doi: 10.1088/1361-6579/aafef2.
  • 47. Griffiths RI, Kotschet K, Arfon S, Xu ZM, Johnson W, Drago J, et al. Automated assessment of bradykinesia and dyskinesia in Parkinson's disease. Journal of Parkinson's disease. 2012;2(1):47-55. doi: 10.3233/JPD-2012-11071.
  • 48. Kassavetis P, Saifee TA, Roussos G, Drougkas L, Kojovic M, Rothwell JC, et al. Developing a tool for remote digital assessment of Parkinson's disease. Movement disorders clinical practice. 2016;3(1):59-64. doi: 10.1002/mdc3.12239.
  • 49. Ferreira JJ, Godinho C, Santos AT, Domingos J, Abreu D, Lobo R, et al. Quantitative home-based assessment of Parkinson’s symptoms: The SENSE-PARK feasibility and usability study. BMC neurology. 2015;15:1-7. doi: 10.1186/s12883-015-0343-z.
  • 50. Lord S, Galna B, Godfrey A, Burn D, Rochester L, editors. Patterns of daily ambulatory activity differ in early Parkinson's disease compared with controls. 16th International Congress of Parkinson's Disease and Movement Disorders; 2012: Newcastle University.
  • 51. Goetz CG, Tilley BC, Shaftman SR, Stebbins GT, Fahn S, Martinez‐Martin P, et al. Movement Disorder Society‐sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS‐UPDRS): scale presentation and clinimetric testing results. Movement disorders: official journal of the Movement Disorder Society. 2008;23(15):2129-70. doi: 10.1002/mds.22340.
  • 52. Galna B, Barry G, Jackson D, Mhiripiri D, Olivier P, Rochester L. Accuracy of the Microsoft Kinect sensor for measuring movement in people with Parkinson's disease. Gait & posture. 2014;39(4):1062-8. doi: 10.1016/j.gaitpost.2014. 01.008.
  • 53. Arora S, Venkataraman V, Zhan A, Donohue S, Biglan KM, Dorsey ER, et al. Detecting and monitoring the symptoms of Parkinson's disease using smartphones: A pilot study. Parkinsonism & related disorders. 2015;21(6):650-3. doi: 10.1016/j.parkreldis.2015.02.026.
  • 54. De Venuto D, Annese VF, Mezzina G, Defazio G. FPGA-based embedded cyber-physical platform to assess gait and postural stability in Parkinson’s disease. IEEE Transactions on Components, Packaging and Manufacturing Technology. 2018;8(7):1167-79. doi: 10.1109/TCPMT.2018.2810103
  • 55. Bansal SK, Basumatary B, Bansal R, Sahani AK. Techniques for the detection and management of freezing of gait in Parkinson's disease–A systematic review and future perspectives. MethodsX. 2023;10:102106. doi: 10.1016/j.mex.2023.102106.
  • 56. Giladi N, Kao R, Fahn S. Freezing phenomenon in patients with parkinsonian syndromes. Movement disorders: official journal of the Movement Disorder Society. 1997;12(3):302-5. doi: 10.1002/mds.870120307.
  • 57. Morris J. Accelerometry—A technique for the measurement of human body movements. Journal of biomechanics. 1973;6(6):729-36. doi: 10.1016/0021-9290(73)90029-8.
  • 58. Han JH, Lee WJ, Ahn TB, Jeon BS, Park KS, editors. Gait analysis for freezing detection in patients with movement disorder using three dimensional acceleration system. Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat No 03CH37439); 2003: IEEE. doi: 10.1109/IEMBS. 2003.1279781.
  • 59. Moore ST, MacDougall HG, Ondo WG. Ambulatory monitoring of freezing of gait in Parkinson's disease. Journal of neuroscience methods. 2008;167(2):340-8. doi: 10.1016/j.jneumeth.2007.08.023.
  • 60. Niazmand K, Tonn K, Zhao Y, Fietzek U, Schroeteler F, Ziegler K, et al., editors. Freezing of Gait detection in Parkinson's disease using accelerometer based smart clothes. 2011 IEEE Biomedical Circuits and Systems Conference (BioCAS); 2011: Ieee. doi: 10.1109/BioCAS.2011.6107762.
  • 61. Popovic M, Djuric-Jovicic M, Radovanovic S, Petrovic I, Kostic V. A simple method to assess freezing of gait in Parkinson's disease patients. Brazilian Journal of Medical and Biological Research. 2010;43:883-9. doi: 10.1590/s0100-879x2010007500077.
  • 62. Handojoseno AA, Gilat M, Ly QT, Chamtie H, Shine JM, Nguyen TN, et al., editors. An EEG study of turning freeze in Parkinson's disease patients: The alteration of brain dynamic on the motor and visual cortex. 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC); 2015: IEEE. doi: 10.1109/EMBC.2015.7319910.
  • 63. Delval A, Snijders AH, Weerdesteyn V, Duysens JE, Defebvre L, Giladi N, et al. Objective detection of subtle freezing of gait episodes in Parkinson's disease. Movement Disorders. 2010;25(11):1684-93. doi: 10.1002/mds.23159.
  • 64. Kim H, Lee HJ, Lee W, Kwon S, Kim SK, Jeon HS, et al., editors. Unconstrained detection of freezing of Gait in Parkinson's disease patients using smartphone. 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC); 2015: IEEE. doi: 10.1109/EMBC.2015.7319209.
  • 65.Godino-Llorente J, Shattuck-Hufnagel S, Choi J, Moro-Velázquez L, Gómez-García J. Towards the identification of Idiopathic Parkinson’s Disease from the speech. New articulatory kinetic biomarkers. PloS one. 2017;12(12):e0189583. doi: 10.1371/journal.pone.0189583.
  • 66. Bot BM, Suver C, Neto EC, Kellen M, Klein A, Bare C, et al. The mPower study, Parkinson disease mobile data collected using ResearchKit. Scientific data. 2016;3(1):1-9. doi: 10.1038/sdata.2016.11.

TECHNOLOGY-BASED EVALUATION IN PARKINSONISM

Yıl 2024, Cilt: 46 Sayı: 3, 156 - 163, 30.09.2024
https://doi.org/10.7197/cmj.1512299

Öz

Parkinson's disease is a neurodegenerative disorder characterized by motor and non-motor symptoms that worsen over time. Today, traditional clinical assessment methods are used to monitor disease progression and evaluate treatment responses. However, these methods are subjective and may fail to measure specific conditions. In recent years, thanks to advances in wearable technologies, smart sensors, and data analysis, technology-based approaches to the assessment of patients with Parkinson's disease have gained more attention. With these technologies, objective data can be obtained by monitoring patients' daily activities, motor functions, and symptoms. Motor symptoms such as tremor severity, rigidity, bradykinesia, postural instabilities, freezing phenomenon, and motor parameters of speech impairment can be objectively measured through these technologies. Furthermore, the ability to remotely transmit these data allows patients to be assessed in their own homes and provides continuous feedback to healthcare professionals. This review highlights the importance and potential of technology-based assessment methods in Parkinson's patients and aims to guide future research.

Kaynakça

  • 1. Fahn S. Unified Parkinson's disease rating scale. Recent developments in Parkinson's disease. 1987:153-63.
  • 2. Balestrino R, Schapira A. Parkinson disease. European journal of neurology. 2020;27(1):27-42. doi: 10.1111/ene.14108.
  • 3. Güler, S., Caylan, A., Turan, F. N., & Dağdeviren, N. (2022). Prevalence and Clinical Features of Idiopathic Parkinson’s Disease in Western Turkey. Archives of Neuropsychiatry, 59(2), 98. doi: 10.29399/npa.27486.
  • 4. Pringsheim T, Jette N, Frolkis A, Steeves TD. The prevalence of Parkinson's disease: a systematic review and meta‐analysis. Movement disorders. 2014;29(13):1583-90. doi: 10.1002/ mds.25945.
  • 5. Dorsey ER, Bloem BR. The Parkinson pandemic—a call to action. JAMA neurology. 2018;75(1):9-10. doi: 10.1001/ jamaneurol.2017.3299.
  • 6. Dorsey ER, Elbaz A, Nichols E, Abbasi N, Abd-Allah F, Abdelalim A, et al. Global, regional, and national burden of Parkinson's disease, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. The Lancet Neurology. 2018;17(11):939-53. doi: 10.1016/S1474-4422(18)30295-3.
  • 7. Jankovic J, Tan EK. Parkinson’s disease: etiopathogenesis and treatment. Journal of Neurology, Neurosurgery & Psychiatry. 2020;91(8):795-808. doi: 10.1136/jnnp-2019-322338.
  • 8. Wolters EC. Variability in the clinical expression of Parkinson's disease. Journal of the neurological sciences. 2008;266(1-2):197-203. doi: 10.1016/j.jns.2007.08.016.
  • 9. Hoehn MM. Commentary: Parkinsonism: Onset, progression, and mortality. Neurology. 1998;50:318-. doi: 10.1212/wnl. 50.2.318.
  • 10. Ozanne A, Johansson D, Hällgren Graneheim U, Malmgren K, Bergquist F, Alt Murphy M. Wearables in epilepsy and Parkinson's disease—a focus group study. Acta Neurologica Scandinavica. 2018;137(2):188-94. doi: 10.1111/ane.12798.
  • 11. Qu Y, Zhang T, Duo Y, Chen L, Li X. Identification and quantitative assessment of motor complications in Parkinson’s disease using the Parkinson’s KinetiGraph™. Frontiers in Aging Neuroscience. 2023;15. doi: 10.3389/fnagi.2023.1142268.
  • 12. Espay AJ, Bonato P, Nahab FB, Maetzler W, Dean JM, Klucken J, et al. Technology in Parkinson's disease: challenges and opportunities. Movement Disorders. 2016;31(9):1272-82. doi: 10.1002/mds.26642.
  • 13. Rovini E, Maremmani C, Cavallo F. How wearable sensors can support Parkinson's disease diagnosis and treatment: a systematic review. Frontiers in neuroscience. 2017;11:555. doi: 10.3389/fnins.2017.00555.
  • 14. Di Lazzaro G, Ricci M, Al-Wardat M, Schirinzi T, Scalise S, Giannini F, et al. Technology-based objective measures detect subclinical axial signs in untreated, de novo Parkinson’s disease. Journal of Parkinson's disease. 2020;10(1):113-22. doi: 10.3233/JPD-191758
  • 15. Godinho C, Domingos J, Cunha G, Santos AT, Fernandes RM, Abreu D, et al. A systematic review of the characteristics and validity of monitoring technologies to assess Parkinson’s disease. Journal of neuroengineering and rehabilitation. 2016;13:1-10. doi: 10.1186/s12984-016-0136-7.
  • 16. Özen D, Karakaya MG, Yenişehir S, Çıtak İ. Parkinsonlu Hastalarda Teknoloji Temelli Yürüyüş Değerlendirmelerinin Literatür Analizi Literature Analysis Of Technology-Based Gait Assessment In Patients With Parkinson Disease. Full Text Book.56.
  • 17. Moreau C, Rouaud T, Grabli D, Benatru I, Remy P, Marques A-R, et al. Overview on wearable sensors for the management of Parkinson’s disease. NPJ Parkinson's Disease. 2023;9(1):153. doi: 10.1038/s41531-023-00585-y.
  • 18. Suppa A, Kita A, Leodori G, Zampogna A, Nicolini E, Lorenzi P, et al. L-DOPA and freezing of gait in Parkinson’s disease: Objective assessment through a wearable wireless system. Frontiers in neurology. 2017;8:406. doi: 10.3389/fneur. 2017.00406.
  • 19. Bove F, Di Lazzaro G, Mulas D, Cocciolillo F, Di Giuda D, Bentivoglio AR. A role for accelerometry in the differential diagnosis of tremor syndromes. Functional neurology. 2018;33(1):45. doi: 10.11138/fneur/2018.33.1.045
  • 20. Delrobaei M, Tran S, Gilmore G, McIsaac K, Jog M. Characterization of multi-joint upper limb movements in a single task to assess bradykinesia. Journal of the neurological sciences. 2016;368:337-42. doi: 10.1016/j.jns.2016.07.056.
  • 21. Ricci M, Giannini F, Saggio G, Cenci C, Di Lazzaro G, Pisani A, editors. A novel analytical approach to assess dyskinesia in patients with Parkinson disease. 2018 IEEE international symposium on medical measurements and applications (MeMeA). 2018; (pp. 1-5), IEEE. doi: 10.1109/MeMeA.2018.8438666.
  • 22. Kaya D, Soyukibar TE. Parkinson’s Disease and Parkinsonism. The Journal of Turkish Family Physician. 2022;13(4):182-92. doi: 10.15511/tjtfp.22.00482
  • 23. Jankovic J. Parkinson’s disease: clinical features and diagnosis. Journal of neurology, neurosurgery & psychiatry. 2008;79(4):368-76. doi: 10.1136/jnnp.2007.131045.
  • 24. Kraus P, Lemke M, Reichmann H. Kinetic tremor in Parkinson’s disease–an underrated symptom. Journal of neural transmission. 2006;113:845-53. doi: 10.1007/s00702-005-0354-9.
  • 25. Fleischman DA, Wilson RS, Schneider JA, Bienias JL, Bennett DA. Parkinsonian signs and functional disability in old age. Experimental aging research. 2007;33(1):59-76. doi: 10.1080/03610730601006370.
  • 26. Rigas G, Tzallas AT, Tsipouras MG, Bougia P, Tripoliti EE, Baga D, et al. Assessment of tremor activity in the Parkinson’s disease using a set of wearable sensors. IEEE Transactions on Information Technology in Biomedicine. 2012;16(3):478-87. doi: 10.1109/TITB.2011.2182616.
  • 27. Heldman DA, Jankovic J, Vaillancourt DE, Prodoehl J, Elble RJ, Giuffrida JP. Essential tremor quantification during activities of daily living. Parkinsonism & related disorders. 2011;17(7):537-42. doi: 10.1016/j.parkreldis.2011.04.017.
  • 28. Delrobaei M, Memar S, Pieterman M, Stratton TW, McIsaac K, Jog M. Towards remote monitoring of Parkinson’s disease tremor using wearable motion capture systems. Journal of the neurological sciences. 2018;384:38-45. doi: 10.1016/ j.jns.2017.11.004.
  • 29. Grimaldi G, Manto M-U, Manto M. Tremor: from pathogenesis to treatment: Morgan & Claypool Publishers; 2008.
  • 30. Rahimi F, Bee C, South A, Debicki D, Jog M, editors. Variability of hand tremor in rest and in posture—A pilot study. In 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society; 2011: IEEE. doi: 10.1109/IEMBS.2011.6090067.
  • 31. Braybrook M, O’Connor S, Churchward P, Perera T, Farzanehfar P, Horne M. An ambulatory tremor score for Parkinson’s disease. Journal of Parkinson's disease. 2016;6(4):723-31. doi: 10.3233/JPD-160898.
  • 32. Wile DJ, Ranawaya R, Kiss ZH. Smart watch accelerometry for analysis and diagnosis of tremor. Journal of neuroscience methods. 2014;230:1-4. doi: 10.1016/j.jneumeth.2014.04. 021.
  • 33. Salarian A, Russmann H, Wider C, Burkhard PR, Vingerhoets FJ, Aminian K. Quantification of tremor and bradykinesia in Parkinson's disease using a novel ambulatory monitoring system. IEEE Transactions on biomedical engineering. 2007;54(2):313-22. doi: 10.1109/TBME.2006.886670
  • 34. Tysnes O-B, Storstein A. Epidemiology of Parkinson’s disease. Journal of neural transmission. 2017;124:901-5. doi: 10.1007/s00702-017-1686-y.
  • 35. 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;126:699-710. doi: 10.1007/s00702-019-02017-9.
  • 36. Ferreira-Sánchez MdR, Moreno-Verdú M, Cano-de-La-Cuerda R. Quantitative measurement of rigidity in Parkinson’s disease: a systematic review. Sensors. 2020;20(3):880. doi: 10.3390/s20030880.
  • 37. Gao J, He W, Du L-J, Li S, Cheng L-G, Shih G, et al. Ultrasound strain elastography in assessment of resting biceps brachii muscle stiffness in patients with Parkinson's disease: a primary observation. Clinical Imaging. 2016;40(3):440-4. doi: 10.1016/j.clinimag.2015.12.008.
  • 38. López-de-Celis C, Pérez-Bellmunt A, Bueno-Gracia E, Fanlo-Mazas P, Zárate-Tejero CA, Llurda-Almuzara L, et al. Effect of diacutaneous fibrolysis on the muscular properties of gastrocnemius muscle. PLoS One. 2020;15(12):e0243225. doi: 10.1371/journal.pone.0243225.
  • 39. Kisilewicz A, Madeleine P, Ignasiak Z, Ciszek B, Kawczynski A, Larsen RG. Eccentric exercise reduces upper trapezius muscle stiffness assessed by shear wave elastography and myotonometry. Frontiers in Bioengineering and Biotechnology. 2020;8:928. doi: 10.3389/fbioe.2020.00928.
  • 40. Agyapong-Badu S, Warner M, Samuel D, Stokes M. Practical considerations for standardized recording of muscle mechanical properties using a myometric device: Recording site, muscle length, state of contraction and prior activity. Journal of Musculoskeletal Research. 2018;21(02):1850010. doi: 10.1142/S0218957718500100.
  • 41. Rätsep T, Asser T. Changes in viscoelastic properties of skeletal muscles induced by subthalamic stimulation in patients with Parkinson's disease. Clinical biomechanics. 2011;26(2):213-7. doi: 10.1016/j.clinbiomech.2010.09.014.
  • 42. Gäverth J, Sandgren M, Lindberg PG, Forssberg H, Eliasson A-C. Test-retest and inter-rater reliability of a method to measure wrist and finger spasticity. Journal of rehabilitation medicine. 2013;45(7):630-6. doi: 10.2340/16501977-1160.
  • 43. Zetterberg H, Frykberg GE, Gäverth J, Lindberg P. Neural and nonneural contributions to wrist rigidity in Parkinson’s disease: an explorative study using the NeuroFlexor. BioMed research international. 2015;2015. doi: 10.1155/2015/ 276182.
  • 44. Perera T, Lee W-L, Jones M, Tan JL, Proud EL, Begg A, et al. A palm-worn device to quantify rigidity in Parkinson’s disease. Journal of neuroscience methods. 2019;317:113-20. doi: 10.1016/j.jneumeth.2019.02.006.
  • 45. Reichmann H. Clinical criteria for the diagnosis of Parkinson’s disease. Neurodegenerative diseases. 2010;7(5):284-90. doi: 10.1159/000314478.
  • 46. Lee WL, Sinclair NC, Jones M, Tan JL, Proud EL, Peppard R, et al. Objective evaluation of bradykinesia in Parkinson’s disease using an inexpensive marker-less motion tracking system. Physiological measurement. 2019;40(1):014004. doi: 10.1088/1361-6579/aafef2.
  • 47. Griffiths RI, Kotschet K, Arfon S, Xu ZM, Johnson W, Drago J, et al. Automated assessment of bradykinesia and dyskinesia in Parkinson's disease. Journal of Parkinson's disease. 2012;2(1):47-55. doi: 10.3233/JPD-2012-11071.
  • 48. Kassavetis P, Saifee TA, Roussos G, Drougkas L, Kojovic M, Rothwell JC, et al. Developing a tool for remote digital assessment of Parkinson's disease. Movement disorders clinical practice. 2016;3(1):59-64. doi: 10.1002/mdc3.12239.
  • 49. Ferreira JJ, Godinho C, Santos AT, Domingos J, Abreu D, Lobo R, et al. Quantitative home-based assessment of Parkinson’s symptoms: The SENSE-PARK feasibility and usability study. BMC neurology. 2015;15:1-7. doi: 10.1186/s12883-015-0343-z.
  • 50. Lord S, Galna B, Godfrey A, Burn D, Rochester L, editors. Patterns of daily ambulatory activity differ in early Parkinson's disease compared with controls. 16th International Congress of Parkinson's Disease and Movement Disorders; 2012: Newcastle University.
  • 51. Goetz CG, Tilley BC, Shaftman SR, Stebbins GT, Fahn S, Martinez‐Martin P, et al. Movement Disorder Society‐sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS‐UPDRS): scale presentation and clinimetric testing results. Movement disorders: official journal of the Movement Disorder Society. 2008;23(15):2129-70. doi: 10.1002/mds.22340.
  • 52. Galna B, Barry G, Jackson D, Mhiripiri D, Olivier P, Rochester L. Accuracy of the Microsoft Kinect sensor for measuring movement in people with Parkinson's disease. Gait & posture. 2014;39(4):1062-8. doi: 10.1016/j.gaitpost.2014. 01.008.
  • 53. Arora S, Venkataraman V, Zhan A, Donohue S, Biglan KM, Dorsey ER, et al. Detecting and monitoring the symptoms of Parkinson's disease using smartphones: A pilot study. Parkinsonism & related disorders. 2015;21(6):650-3. doi: 10.1016/j.parkreldis.2015.02.026.
  • 54. De Venuto D, Annese VF, Mezzina G, Defazio G. FPGA-based embedded cyber-physical platform to assess gait and postural stability in Parkinson’s disease. IEEE Transactions on Components, Packaging and Manufacturing Technology. 2018;8(7):1167-79. doi: 10.1109/TCPMT.2018.2810103
  • 55. Bansal SK, Basumatary B, Bansal R, Sahani AK. Techniques for the detection and management of freezing of gait in Parkinson's disease–A systematic review and future perspectives. MethodsX. 2023;10:102106. doi: 10.1016/j.mex.2023.102106.
  • 56. Giladi N, Kao R, Fahn S. Freezing phenomenon in patients with parkinsonian syndromes. Movement disorders: official journal of the Movement Disorder Society. 1997;12(3):302-5. doi: 10.1002/mds.870120307.
  • 57. Morris J. Accelerometry—A technique for the measurement of human body movements. Journal of biomechanics. 1973;6(6):729-36. doi: 10.1016/0021-9290(73)90029-8.
  • 58. Han JH, Lee WJ, Ahn TB, Jeon BS, Park KS, editors. Gait analysis for freezing detection in patients with movement disorder using three dimensional acceleration system. Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat No 03CH37439); 2003: IEEE. doi: 10.1109/IEMBS. 2003.1279781.
  • 59. Moore ST, MacDougall HG, Ondo WG. Ambulatory monitoring of freezing of gait in Parkinson's disease. Journal of neuroscience methods. 2008;167(2):340-8. doi: 10.1016/j.jneumeth.2007.08.023.
  • 60. Niazmand K, Tonn K, Zhao Y, Fietzek U, Schroeteler F, Ziegler K, et al., editors. Freezing of Gait detection in Parkinson's disease using accelerometer based smart clothes. 2011 IEEE Biomedical Circuits and Systems Conference (BioCAS); 2011: Ieee. doi: 10.1109/BioCAS.2011.6107762.
  • 61. Popovic M, Djuric-Jovicic M, Radovanovic S, Petrovic I, Kostic V. A simple method to assess freezing of gait in Parkinson's disease patients. Brazilian Journal of Medical and Biological Research. 2010;43:883-9. doi: 10.1590/s0100-879x2010007500077.
  • 62. Handojoseno AA, Gilat M, Ly QT, Chamtie H, Shine JM, Nguyen TN, et al., editors. An EEG study of turning freeze in Parkinson's disease patients: The alteration of brain dynamic on the motor and visual cortex. 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC); 2015: IEEE. doi: 10.1109/EMBC.2015.7319910.
  • 63. Delval A, Snijders AH, Weerdesteyn V, Duysens JE, Defebvre L, Giladi N, et al. Objective detection of subtle freezing of gait episodes in Parkinson's disease. Movement Disorders. 2010;25(11):1684-93. doi: 10.1002/mds.23159.
  • 64. Kim H, Lee HJ, Lee W, Kwon S, Kim SK, Jeon HS, et al., editors. Unconstrained detection of freezing of Gait in Parkinson's disease patients using smartphone. 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC); 2015: IEEE. doi: 10.1109/EMBC.2015.7319209.
  • 65.Godino-Llorente J, Shattuck-Hufnagel S, Choi J, Moro-Velázquez L, Gómez-García J. Towards the identification of Idiopathic Parkinson’s Disease from the speech. New articulatory kinetic biomarkers. PloS one. 2017;12(12):e0189583. doi: 10.1371/journal.pone.0189583.
  • 66. Bot BM, Suver C, Neto EC, Kellen M, Klein A, Bare C, et al. The mPower study, Parkinson disease mobile data collected using ResearchKit. Scientific data. 2016;3(1):1-9. doi: 10.1038/sdata.2016.11.
Toplam 66 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Birinci Basamak Sağlık Hizmetleri, Sağlık ve Toplum Hizmetleri
Bölüm Derlemeler
Yazarlar

Selvin Balki 0000-0003-4903-6349

Emine Nacar 0000-0002-1172-1837

Rabia Seva Özkan 0000-0001-9892-5949

Merve Karakurt 0000-0002-3370-7526

Yayımlanma Tarihi 30 Eylül 2024
Gönderilme Tarihi 8 Temmuz 2024
Kabul Tarihi 10 Ağustos 2024
Yayımlandığı Sayı Yıl 2024Cilt: 46 Sayı: 3

Kaynak Göster

AMA Balki S, Nacar E, Özkan RS, Karakurt M. TECHNOLOGY-BASED EVALUATION IN PARKINSONISM. CMJ. Eylül 2024;46(3):156-163. doi:10.7197/cmj.1512299