Comparative Study of Needle Sensations in ST and 6 Models with Quantifying Measurement System

Ye Ji Han; Su Jeong Jo; Young Nam Son; Soo Yoon Lee; Kap Sung Kim; Seung Deok Lee

doi:10.13045/acupunct.2013048

J Acupunct Res > Volume 30(5); 2013 > Article

Han, Jo, Son, Lee, Kim, and Lee: Comparative Study of Needle Sensations in ST36 and 6 Models with Quantifying Measurement System※

Original Article

The Acupuncture 2013; 30(5): 87-94.

Published online: December 20, 2013

DOI: https://doi.org/10.13045/acupunct.2013048

Comparative Study of Needle Sensations in ST₃₆ and 6 Models with Quantifying Measurement System^※

Ye Ji Han¹, Su Jeong Jo², Young Nam Son¹, Soo Yoon Lee¹, Kap Sung Kim², Seung Deok Lee^2,^*

¹College of Oriental Medicine, Dongguk University

²Department of Acupuncture & Moxibustion Medicine, Dongguk University International Hospital

Supported by:

^※ This study was supported by a grant of the Traditional Korean Medicine R&D Project, Ministry of Health & Welfare, Republic of Korea(B110069)

Supported by:

^※ This study was supported by the “2013 KIOM Undergraduate Research Program” funded by Korea Institute of Oriental Medicine(C13080)

^*Corresponding author : Department of Acupuncture &Moxibustion Medicine, Dongguk University International Hospital, 814, Siksa-dong, Ilsandong-gu, Goyang-si, Gyeonggi-do, 410-773, Republic of Korea,
Tel: +82-31-961-9122 E-mail: chuckman@dongguk.edu

Received November 07, 2013 Revised November 29, 2013 Accepted December 03, 2013

This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

See the Original "".

Abstract

Objectives:

In this study, we intended to make the foundation of the development of acupuncture tissue model as comparing the needle sensation of six kinds of tissue models and Zusanli (ST₃₆) with the needle force measurement system.

Methods:

When practitioners did twisting-rotating acupuncture needle manipulation after inserting the needle into six kinds of tissue models, they quantified the similarity sense to the sensation of Zusanli (ST₃₆) with the NRS (Numeric Rating scale).

As needle force measurement system did twisting-rotating Acupuncture needle manipulation after inserting needle into Zusanli (ST₃₆) of human and six kinds of tissue models, it can calculate the coefficient of viscosity by measuring the torsion friction.

We compare the NRS of practitioners’ needle sensation to the coefficient of viscosity of needle force measurement systems.

Result:

As practitioners’ NRS assessment to quantify needle sensation, apple and cucumber showed 70% similarity to Zusanli (ST₃₆). As needle force measurement system’s coefficient of viscosity, apple and cucumber’s coefficient of viscosity were similar to Zusanli (ST₃₆) ’s.

Conclusions:

In this study, We compared the practitioners’ needle sensation of Zusanli (ST₃₆) and six kinds of tissue models with needle force measurement system that can quantify the needle sensation. As the result, we concluded that practitioners’ needle sensation is similar to measured needle sensation. It seems that the acupuncture practice model implementing the needle sensation to specific acupuncture points can be built based on the system in this study.

Key Words: Acupuncture practice; Manipulation; Needle force; Needle sensation; Tissue model.

Fig. 1.

Experimental setup for data collection under needle force measuring system

The tissue model is suspended in tissue container, and small holes on the container allow the needle to pass through.

Fig. 2.

Diagram of torque Z forces

Toque Z forces detected by motion and force sensors needle ‘force’ is the linear force acting on the needle parallel to its longitudinal axis; needle ‘torque’ is the rotational force(torque) acting on the needle to resist its rotation.

Fig. 3.

Blind box

A·B·C : people. 1·2·3 : number of experiments.

Fig. 4.

Needle tissue model group-specific changes over time graph

(a) Changes in torque Z axis friction.

(b) Changes in the angle of rotation.

Fig. 5.

Needle tissue model group-specific coefficient of viscosity

Data are presented as mean.

p< 0.05 by Bartlett’s test for equal variances after one-way ANOVA.

Table 1.

NRS Value of Similarity between ST₃₆ and Tissue Model by Practitioners

Tissue model	Mean±SD	Minimum	Maximum
Agar gel	1.00±0	1	1
Ham	2.00±1	1	3
Sweet potato	3.89±1.27	2	6
Carrot	4.00±1.22	3	6
Cucumber	7.89±1.76	4	10
Apple	6.89±2.76	2	10

SD : standard deviation.

Table 2.

Coefficient of Viscosity in Tissue Model Group

Tissue model	Mean±SD	Maximum	Minimum
Agar gel	−6.6±44.14	46.7	−76.9
Ham	76.14±17.97	106.4	42.4
Sweet potato	6282.77±367.34	6965.1	5813.2
Carrot	5191.04±293.31	5599	4738.4
Cucumber	1189.31±25.81	1226.9	1132.4
Apple	1406.05±85.96	1540.5	1297.2
Human(ST₃₆)	1267.58±107.06	1455.2	1106.6

The number is coefficient of viscosity X 106.

SD : standard deviation.

VI. References

1. Suh EY. Development of a Conceptual Framework for Nursing Simulation Education Utilizing Human Patient Simulators and Standardized Patients. J Korean Acad Soc Nurs Edu. 2012;18(2):206–19.

2. Wong V, Cheuk DK, Lee S, Chu V. Acupuncture for acute management and rehabilitation of traumatic brain injury. Cochrane Database Syst Rev. 2011;(5):

3. Park HK. Medical Education Using Standardized Patients. Hanyang Medical Reviews. 2012;32(1):35–44.

4. Park HK, Kim DW, Kim DA, Choi HS, Kim KT. An OSCE assessment of fourth-year medical students as a comprehensive evaluation of medical skills before graduation. Korean Journal of Medical Education. 1998;10(1):43–56.

5. Taylor CA, Green KE. OSCE Feedback: A Randomized Trial of Effectiveness, Cost-Effectiveness and Student Satisfaction. Sci Res. 2013;4(6):9–14.

6. Son IC. Study on the Process of manufacture of Standard Acu-Figure. The Acupuncture. 2000;17(1):13–25.

7. Son IC. The Reserch of Alternation and Development of Acu-Figure. The Acupuncture. 1998;15(2):551–63.

8. Cabyoglu MT, Ergene N, Tan U. The mechanism of acupuncture and clinical applications. Int J Neurosci. 2006;116(2):115–25.

9. Napadow V, Kettner N, Liu J, Li M, Kwong KK, Vangel M, et al. Hypothalamus and amygdala response to acupuncture stimuli in Carpal Tunnel Syndrome. Pain. 2007;130(3):254–66.

10. Hui KK, Sporko TN, Vangel MG, Li M, Fang J, Lao L. Perception of Deqi by Chinese and American acupuncturists: a pilot survey. Chin Med. 2011;6(1):2.

11. Mackereth PA, Maycock P. Needling Techniques for Acupuncturists: Basic Principles and Techniques. Complement Ther Clin Pract. 2012;18(2):129.

12. Kong J, Gollub R, Huang T, et al. Acupuncture de qi, from qualitative history to quantitative measurement. J Altern Complement Med. 2007;13(10):1059–70.

13. MacPherson H, Asghar A. Acupuncture needle sensations associated with De Qi: a classification based on experts’ ratings. J Altern Complement Med. 2006;12(7):633–7.

14. Mao JJ, Farrar JT, Armstrong K, Donahue A, Ngo J, Bowman MA. De qi: Chinese acupuncture patients’ experiences and beliefs regarding acupuncture needling sensation--an exploratory survey. Acupunct Med. 2007;25(4):158–65.

15. Lin C, Yuan HW, Zhang P, et al. Review of studies on De qi of acupuncture mainly in foreign countries. Zhen Ci Yan Jiu. 2013;38(2):168–73.

16. Li ZG, Wu MM, Liu CZ. Progress of researches on acupuncture manipulation and its quantification. Zhen Ci Yan Jiu. 2010;35(1):78–81.

17. Chaudhury RR, Rafei UM. Traditional medicine in Asia. New Delhi: World Health Organization. 2002:26–27.

18. White A, Cummings M, Barlas P, et al. Defining an adequate dose of acupuncture using a neuro-physiological approach-a narrative review of the literature. Acupunct Med. 2008;26(2):111–20.

19. Reed KB, Okamura AM, Cowan NJ. Modeling and control of needles with torsional friction. IEEE Trans Biomed Eng. 2009;56(12):2905–16.

20. Ernst E. Acupuncture therapy for neurological diseases. Focus Alternat Complement Ther. 2010;15(4):339.

21. Bradley P. The history of simulation in medical education and possible future directions. Med Educ. 2006;40(3):254–62.

22. Misra S, Reed KB, Douglas AS, Ramesh KT, Okamura AM. Needle-Tissue Interaction Forces for Bevel-Tip Steerable Needles. BioRob 2008. In: 2nd IEEE RAS & EMBS International Conference; Oct 19–22; Scottsdale, USA: Biomedical Robotics and Biomechatronics. 2008;

23. Reed KB, Okamura AM, Cowan NJ. Controlling a Robotically Steered Needle in the Presence of Torsional Friction ICRA ‘09. In: IEEE International Conference; 2009 May 12–17; Kobe, Japan: Robotics and Automation. 2009;

24. Brett PN, Harrison AJ, Thomas TA. Schemes for the identification of tissue types and boundaries at the tool point for surgical needles. IEEE Trans Inf Technol Biomed. 2000;4(1):30–6.

25. Brett PN, Parker TJ, Harrison AJ, Thomas TA, Carr A. Simulation of resistance forces acting on surgical needles. Journal of Engineering in Medicine. 1997;211(4):335–47.

26. Holton LL. Force models for needle insertion created from measured needle puncture data. Edited by Westwood JD, Hoffman HM, Mogel GT, Stredney D, Robb RA. In: Medicine Meets Virtual Reality 2001. Neherlands: IOS Press. 2001:180–6.

27. Nakamachi E. Development of automatic operated blood sampling system for portable type Self- Monitoring Blood Glucose device. In: 2010 Annual International Conference of the IEEE; 2010 Aug 31–Sep 4; Buenos Aires, Argentina: Engineering in Medicine and Biology Society(EMBC). 2010;

28. Langevin HM, Bouffard NA, Churchill DL, Badger GJ. Connective tissue fibroblast response to acupuncture: dose-dependent effect of bidirectional needle rotation. J Altern Complement Med. 2007;13(3):355–60.

29. Wang C, Xu J, Zhang T. Study on twirling reinforcing-reducing manipulation based on the parameter figure of the acupuncture manipulation apparatus. Zhongguo Zhen Jiu. 2009;29(9):723–5.

30. Wedlick TR, Okamura AM. Characterization of robotic needle insertion and rotation in artificial and ex vivo tissues. 2012;In: 4th IEEE RAS & EMBS International Conference; 2012 June 24–27; Rome, Italy: Biomedical Robotics and Biomechatronics. 2012;