A mechanical impedance-based measurement system for quantifying Parkinsonian rigidity_Journal of Biomedical Engineering

Authors：

DAI Houde ¹ , XIONG Yongsheng ^1,2 , CAI Guoen ³ , XIA Xuke ¹ ,  LIN Zhirong ¹

1. Quanzhou Institute of Equipment Manufacturing, Haixi Institutes, Chinese Academy of Sciences, Jinjiang, Fujian 362200, P.R.China;
2. School of Electrical and Control Engineering, North University of China, Taiyuan 030051, P.R.China;
3. Neurology Department, Affiliated Union Hospital of Fujian Medical University, Fuzhou 350001, P.R.China;

Corresponding author：

LIN Zhirong, Email: linzhirong@fjirsm.ac.cn

Keywords：

Parkinson’s disease; rigidity; mechanical impedance; quantitative assessment

DOI：

10.7507/1001-5515.201708069

Video：

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At present the parkinsonian rigidity assessment depends on subjective judgment of neurologists according to their experience. This study presents a parkinsonian rigidity quantification system based on the electromechanical driving device and mechanical impedance measurement method. The quantification system applies the electromechanical driving device to perform the rigidity clinical assessment tasks (flexion-extension movements) in Parkinson’s disease (PD) patients, which captures their motion and biomechanical information synchronously. Qualified rigidity features were obtained through statistical analysis method such as least-squares parameter estimation. By comparing the judgments from both the parkinsonian rigidity quantification system and neurologists, correlation analysis was performed to find the optimal quantitative feature. Clinical experiments showed that the mechanical impedance has the best correlation (Pearson correlation coefficient r = 0.872, P < 0.001) with the clinical unified Parkinson’s disease rating scale (UPDRS) rigidity score. Results confirmed that this measurement system is capable of quantifying parkinsonian rigidity with advantages of simple operation and effective assessment. In addition, the mechanical impedance can be adopted to help doctors to diagnose and monitor parkinsonian rigidity objectively and accurately.

Citation： DAI Houde, XIONG Yongsheng, CAI Guoen, XIA Xuke, LIN Zhirong. A mechanical impedance-based measurement system for quantifying Parkinsonian rigidity. Journal of Biomedical Engineering, 2018, 35(3): 421-428. doi: 10.7507/1001-5515.201708069 Copy

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2.	刘疏影, 陈彪. 帕金森病流行现状. 中国现代神经疾病杂志, 2016, 16(2): 98-101.
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8.	陈薇, 谢惠君, 汪剑. 磁共振波谱分析在帕金森病早期诊断应用中的价值. 中国临床康复, 2004, 8(1): 34-35.
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14.	Maetzler W, Domingos J, Srulijes K, et al. Quantitative wearable sensors for objective assessment of Parkinson's disease. Mov Disord, 2013, 28(12): 1628-1637.
15.	Sepehri B, Esteki A, Ebrahimi-Takamjani E, et al. Quantification of rigidity in Parkinson's disease. Ann Biomed Eng, 2007, 35(12): 2196-2203.
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19.	焦根龙, 李志忠, 潘永勤. 肘关节复合畸形并多发性脱位、关节不稳的手术治疗. 中华创伤骨科杂志, 2008, 10(3): 299-300.
20.	Fong W T, Ong S K, Nee A . Methods for in-field user calibration of an inertial measurement unit without external equipment. Measurement Science and Technology, 2008, 19(8): 817-822.
21.	左鹤声. 机械阻抗方法与应用. 北京: 机械工业出版社, 1987: 1-475.
22.	王帅杰, 左国坤. 在线调整对到达运动中人体上肢刚性特性的影响. 医用生物力学, 2015, 30(04): 355-360, 372.
23.	Dorrington K L, 孙家驹, 马若涓. 生物材料的粘弹性理论. 力学进展, 1988, 18(3): 106-119.
24.	王福昌, 曹慧荣, 朱红霞. 经典最小二乘与全最小二乘法及其参数估计. 统计与决策, 2009(1): 16-17.
25.	Park B K, Kwon Y, Kim J W, et al. Analysis of viscoelastic properties of wrist joint for quantification of parkinsonian rigidity. IEEE Trans Neural Syst Rehabil Eng, 2011, 19(2): 167-176.
26.	周颖, 龚顺明, 吕西林. 黏弹性阻尼器滞回曲线及特征参数的相似准则. 中南大学学报:自然科学版, 2014(12): 4317-4324.

1. Zhang Zhenxin, Roman G C, Hong Zhen, et al. Parkinson's disease in China: prevalence in Beijing, Xian, and Shanghai. Lancet, 2005, 365(9459): 595-597.
2. 刘疏影, 陈彪. 帕金森病流行现状. 中国现代神经疾病杂志, 2016, 16(2): 98-101.
3. Jankovic J. Parkinson's disease: clinical features and diagnosis. J Neurol Neurosurg Psychiatry, 2008, 79(4): 368-376.
4. 中华医学会神经病学分会运动障碍及帕金森病学组. 帕金森病的诊断. 中华神经科杂志, 2006, 39(6): 408-409.
5. Deuschl G, Schade-Brittinger C, Krack P, et al. A randomized trial of deep-brain stimulation for Parkinson's disease. N Engl J Med, 2006, 355(9): 896-908.
6. Goetz C G, Tilley B C, Shaftman S R, 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, 2008, 23(15): 2129-2170.
7. 王荣丽, 王宁华, 谢斌. 表面肌电图在帕金森病中的应用. 中国康复理论与实践, 2012, 18(02): 144-148.
8. 陈薇, 谢惠君, 汪剑. 磁共振波谱分析在帕金森病早期诊断应用中的价值. 中国临床康复, 2004, 8(1): 34-35.
9. 李亮, 俞乾, 徐宝腾, 等. 帕金森病患者多节点运动监测可穿戴设备. 生物医学工程学杂志, 2016, 33(06): 1183-1190.
10. Giuffrida J P, Riley D E, Maddux B N, et al. Clinically deployable Kinesia technology for automated tremor assessment. Mov Disord, 2009, 24(5): 723-730.
11. Heldman D A, Giuffrida J P, Chen R, et al. The modified bradykinesia rating scale for Parkinson's disease: reliability and comparison with kinematic measures. Mov Disord, 2011, 26(10): 1859-1863.
12. Cole B T, Roy S H, de Luca C J, et al. Dynamical learning and tracking of tremor and dyskinesia from wearable sensors. IEEE Trans Neural Syst Rehabil Eng, 2014, 22(5): 982-991.
13. Martinez-Manzanera O, Roosma E, Beudel M, et al. A method for automatic and objective scoring of bradykinesia using orientation sensors and classification algorithms. IEEE Trans Biomed Eng, 2016, 63(5): 1016-1024.
14. Maetzler W, Domingos J, Srulijes K, et al. Quantitative wearable sensors for objective assessment of Parkinson's disease. Mov Disord, 2013, 28(12): 1628-1637.
15. Sepehri B, Esteki A, Ebrahimi-Takamjani E, et al. Quantification of rigidity in Parkinson's disease. Ann Biomed Eng, 2007, 35(12): 2196-2203.
16. Endo T, Okuno R, Yokoe M, et al. A novel method for systematic analysis of rigidity in Parkinson's disease. Mov Disord, 2009, 24(15): 2218-2224.
17. Xia Ruiping, Sun Junfeng, Threlkeld A J. Analysis of interactive effect of stretch reflex and shortening reaction on rigidity in Parkinson's disease. Clin Neurophysiol, 2009, 120(7): 1400-1407.
18. Patrick S K, Denington A A, Gauthier M J, et al. Quantification of the UPDRS rigidity scale. IEEE Trans Neural Syst Rehabil Eng, 2001, 9(1): 31-41.
19. 焦根龙, 李志忠, 潘永勤. 肘关节复合畸形并多发性脱位、关节不稳的手术治疗. 中华创伤骨科杂志, 2008, 10(3): 299-300.
20. Fong W T, Ong S K, Nee A . Methods for in-field user calibration of an inertial measurement unit without external equipment. Measurement Science and Technology, 2008, 19(8): 817-822.
21. 左鹤声. 机械阻抗方法与应用. 北京: 机械工业出版社, 1987: 1-475.
22. 王帅杰, 左国坤. 在线调整对到达运动中人体上肢刚性特性的影响. 医用生物力学, 2015, 30(04): 355-360, 372.
23. Dorrington K L, 孙家驹, 马若涓. 生物材料的粘弹性理论. 力学进展, 1988, 18(3): 106-119.
24. 王福昌, 曹慧荣, 朱红霞. 经典最小二乘与全最小二乘法及其参数估计. 统计与决策, 2009(1): 16-17.
25. Park B K, Kwon Y, Kim J W, et al. Analysis of viscoelastic properties of wrist joint for quantification of parkinsonian rigidity. IEEE Trans Neural Syst Rehabil Eng, 2011, 19(2): 167-176.
26. 周颖, 龚顺明, 吕西林. 黏弹性阻尼器滞回曲线及特征参数的相似准则. 中南大学学报:自然科学版, 2014(12): 4317-4324.

Journal of Biomedical Engineering

A mechanical impedance-based measurement system for quantifying Parkinsonian rigidity

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