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대퇴 및 하퇴 골절정복수술 견인보조시 관절부하 평가

배태수1,#orcid, 조병찬1, 한재웅2

Evaluation of Joint Load as Pre-Operative Traction in Fracture Reduction Surgeries of Femur and Tibia

Tae Soo Bae1,#orcid, Byeong Chan Cho1, Jae Woong Han2
Journal of the Korean Society for Precision Engineering 2019;36(10):983-988.
Published online: October 1, 2019

1 중원대학교 생체의공학과

2 고려대학교 기계공학부

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#E-mail: bmebae@jwu.ac.kr, TEL: +82-43-830-8610
• Received: January 10, 2019   • Revised: April 22, 2019   • Accepted: July 9, 2019

Copyright © The Korean Society for Precision Engineering

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.

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  • Safe pre-operative traction applied and maintained to the fractured site in fracture reduction surgery is crucial. However, existing traction techniques performed by clinicians or manual traction devices are not elaborate and have no traction force information considering differences in patients’ bodies. The purpose of this study was to evaluate joint loads of fractured sites as pre-operative traction forces considering body mass index (BMI) during fracture reduction surgeries using a robot-assisted device. We developed a lower-extremity dummy model to measure joint loads at hip, knee, ankle, and fractured sites. In 240 cases, four BMI types, six traction forces and two fractured sites were used. Results showed that joint load on major joints decreased as BMI increased. Additionally, joint load increased proportionally in the fractured tibia, but showed inverse tendency in the fractured femur. Control errors of up to 20% in repetitive control and approximately 30% in random control were measured, in comparison to estimated joint loads. Control error increased as traction force decreased. It is possible that applicability of robot systems to safe and precise surgical assistance can be validated. More precise traction control and real-time traction load monitoring technology will enable replacement of traction techniques in the near future.
  • KEYWORDS: Fracture reduction, Traction force, Joint load, Traction robot
  • KEYWORDS: 골절정복, 견인력, 관절부하, 견인 로봇
골절정복 수술에서는 안정적인 수술을 위해 골절된 부위에 제어가 가능한 견인력이 필요하다. 보통 수술 현장에서는 견인력 부하를 위해 골절테이블을 사용하나, 골절테이블을 사용할 때 환부 고정의 불편함과 환자 자세에 대한 자유도 제한 등의 이유로 의료장비보다는 전문의료인력이 직접 환부에 견인력을 주면서 골절정복 수술을 하고 있는 실정이다. 이럴 경우 전문의료인력의 추가 투입에 따른 비용손실과 더불어 필요한 견인력 크기, 견인자세, 그리고 견인유지시간 등에 따라 전문의료인력의 피로감 증대로 인해 사고위험 가능성이 높아지게 된다.
골절정복 수술의 경우 골절된 환부에 제어가 가능한 견인력이 적용되는 것이 중요한데, 이를 해결하기 위하여 다수의 수술항법장치와 견인로봇시스템에 대한 연구가 진행되었다. Markus 등은 2D 투시영상을 이용한 기존의 골절정복 술법과 3D 영상을 이용하는 로봇지원 골절정복 술법의 결과를 상호 비교했을 때, 전자의 정밀도가 높다는 것을 보고하였다.1 Graham 등은 헥사포드 형태의 병렬 로봇을 사용하여 골절 정복을 시도했다.2 Joung 등은 6축을 갖는 전용의 골절 로봇을 이용하여 골절 정복에 관련된 안전성 문제를 풀려고 시도하였다.3 Ye 등은 병렬로봇과 직렬로봇의 장점을 택한 하이브리드 타입의 골절 정복을 위한 로봇을 보고하였으나, 설계 이외의 실험 결과를 보여주지는 못했다.4
따라서 본 연구에서는 골절정복 수술에 적용가능한 견인로봇시스템을 개발하는 과정에서 견인로봇의 제어 성능 및 임상에서 적용가능한 관절부하를 제안하고자 하였다.
2.1 인체 더미모델 제작
인체 더미모델은 각 하퇴부와 대퇴부에 골절이 되었다는 가정하에 골절모델로 제작되었다. 재질은 Steel로 제작되었으며, 인체 더미모델의 길이와 무게는 한국인의 인체치수 (Size Korea 2015, 국가기술표준원)에서 제시하는 남성 19-60세의 분절 길이 및 무게를 기초로 하였다. 또한 골절 더미모델은 길이조절 및 무게조절, 골반 폭조절이 가능하도록 모듈형태로 설계 하였다. 골절 더미모델의 최소길이는 750 mm에서 950 mm까지 구현이 가능하며, 무게의 경우 최소 10 kg에서 최대 22.5 kg까지 구현이 가능하게 설계하였다(Fig. 1).
Fig. 1

Assembly of multi-segment dummy including fractured femur and fractured tibia segments

KSPE_2019_v36n10_983_f001.jpg
2.2 BMI별 견인력 및 관절별 제어 평가
실험은 각 신체비만지수(Body Mass Index, BMI)에 따라 관절별 제어성능을 평가하였으며, 인체모델의 범위는 저체중(Under Weight, BMI < 18.5 kg/m2)부터 정상체중(Normal Weight, 18.5 kg/m2 < BMI < 24.9 kg/m2), 과체중(Over Weight, 18.5 kg/m2 < BMI < 24.9 kg/m2), 비만체중(Obese Weight, 30.0 kg/m2 < BMI)까지 4가지의 BMI군을 적용하였다. BMI는 각 지정한 신장 및 체중 범위 내의 BMI별 5가지 총 20가지 경우를 선정하였다(Table 1).
Table 1

Experimental groups according to body mass index

Table 1
Under weight Normal weight
Height
(m)		 Weight
(kg)		 BMI
(kg/m2)		 Height
(m)		 Weight
(kg)		 BMI
(kg/m2)
1.63 43 16.18 1.63 52 19.57
1.58 43 17.22 1.73 60 20.05
1.73 52 17.37 1.58 52 20.93
1.53 43 18.37 1.68 60 21.26
1.68 52 18.42 1.53 52 22.21
Over weight Obese weight
Height
(m)		 Weight
(kg)		 BMI
(kg/m2)		 Height
(m)		 Weight
(kg)		 BMI
(kg/m2)
1.93 95 25.50 1.78 95 30.12
1.83 86 25.68 1.93 104 31.05
1.88 95 26.88 1.73 95 31.74
1.78 86 27.14 1.78 104 32.82
1.73 86 28.73 1.73 104 34.75
실험간 관절별 부하를 측정하기 위하여 부하측정 전용프로그램(LM 2005, Cas Korea)을 이용하였으며, Ch1부터 Ch9까지 총 9개의 채널을 사용하였다. 로드셀은 각 관절부위와 골절부위의 부하값을 확인하기 위해 사용하였으며, 로드셀은 양하지의 고관절, 슬관절, 족관절, 대퇴 골절부위, 하퇴 골절부위에 인장 로드셀(8개)를 배치하였다. 또한 견인력 적용시 서혜부에 미치는 영향을 측정하기 위해 추가로 서혜부에 로드셀 1개를 설치하여, 총 9개의 로드셀을 설치하였다. 견인력은 각 BMI별로 하지 원위부에 일정한 견인력(50, 100, 150, 200, 250, 300N)을 적용시킨 후 로드셀에서 측정되는 부하값을 측정하였다(Fig. 2).
Fig. 2

Experimental setup for traction robot with the dummy model

KSPE_2019_v36n10_983_f002.jpg
2.3 골절부에 대한 반복 제어성능 실험
선정된 각 BMI군에서 중간 BMI인 신장 173 cm에 체중 52 kg (BMI: 17.4), 신장 158 cm에 체중 52 kg (BMI: 20.9), 신장 188 cm에 체중 95 kg (BMI: 26.9), 신장 173 cm에 체중 52 kg (BMI: 31.7)로서 총 4가지 경우를 선정하였다(Table 2). 견인로봇의 반복적인 골절부 제어성능을 평가하기 위하여 각 BMI별로 3회씩 반복실험을 실시하였다.
Table 2

Selection of human dummy models for repeated control performance test

Table 2
Group Height (m) Weight (kg) BMI (kg/m2)
Under weight 1.73 52 17.37
Normal weight 1.58 52 20.93
Over weight 1.88 95 26.88
Obese weight 1.73 95 31.74
2.4 골절부에 대한 랜덤 제어성능 실험
반복 제어성능 실험 이후에 선정된 20가지의 BMI를 제외한 상태에서 하퇴 골절더미와 대퇴 골절 더미모델의 BMI를 추가로 랜덤하게 설정하였다. 그리고 견인로봇의 랜덤한 BMI에 대한 골절부 제어성능을 평가하기 위하여 하퇴 골절더미와 대퇴골절더미 모델을 각각 4가지 경우를 설정하였고, 총 8가지 BMI에 대해 제어성능 실험을 실시하였다(Table 3).
Table 3

Selection of human dummy models for random control performance test

Table 3
Fractured tibia dummy Fractured femur dummy
Height
(m)		 Weight
(kg)		 BMI
(kg/m2)		 Height
(m)		 Weight
(kg)		 BMI
(kg/m2)
1.78 52 16.4 1.83 52 15.5
1.93 86 23.1 1.58 60 24.1
1.83 95 28.4 1.53 60 25.6
1.63 86 32.4 1.68 104 36.9
3.1 BMI에 따른 관절별 제어성능 실험 결과
하퇴 골절모델에 대한 실험결과 고관절과 슬관절 및 서혜부는 BMI가 증가할수록 관절 부하값이 반비례 하는 경향을 나타내었으며, 족관절은 유의한 경향이 나타나지 않았다. 반면에, 골절부는 BMI가 증가함에 따라 작용하는 부하값이 비례하여 증가하는 경향이 나타났다.
또한 대퇴 골절모델에 대한 실험결과 고관절 및 서혜부는 BMI가 증가할수록 작용하는 부하값이 반비례 하는 경향을 나타내는 반면에 슬관절은 비례하는 경향을 보였으며, 족관절은 유의한 경향이 나타나지 않았다. 반면, 골절부는 회귀식을 보았을 때 BMI이 증가함에 따라 작용 하는 부하값이 반비례적으로 감소하는 경향이 나타났다(Fig. 3).
Fig. 3

Joint forces during each traction force (50-300 N) applied to fractured tibia and fractured femur of the dummy. For each traction force, upper figure showed joint force of fractured tibia and lower figure showed that of fractured femur repectively

KSPE_2019_v36n10_983_f003.jpg
견인력을 50 N에서 300 N으로 증가할 때 골절부위에 걸리는 부하에 대한 회귀 분석결과 견인력이 증가할수록 결정계수(R2)값이 높아지는 것을 보았을 때, 관절부하와의 선형성(Linearity)이 증가함으로 제어성능이 개선된다는 것을 확인하였다.
3.2 골절부에 대한 반복 제어성능 실험 결과
골절부의 BMI별 회귀식에 대한 반복제어 3회 실험 측정값의 근사도를 반복제어 3회 실험 부하의 평균값과 BMI별 회귀식에 BMI를 대입한 값을 비교함으로써 반복 제어성능을 비교하였다. 그 결과, 하퇴 골절부에서는 견인력 대비 모든 BMI에 대해 평균적으로 10% 미만의 반복 제어오차를 나타냈으며, 대퇴 골절부에서는 견인력 300 N의 경우를 제외하고는 모두 평균적으로 10% 이상의 반복 제어오차를 보였다 또한 견인력 50 N에서 제일 높은 반복 제어오차(21.35%)를 보이는 것으로 나타났다(Fig. 4).
Fig. 4

Approximate rate of the repeated experiment to the BMI trend line for fractured tibia (up) and fractured femur (down) dummy

KSPE_2019_v36n10_983_f004.jpg
반복 제어오차에 대한 편차는 하퇴 골절부의 경우 견인력이 증가함에 따라 편차가 증가하는 양상을 보였으나, 대퇴 골절모델의 경우에는 반대의 양상을 보였다. 따라서 대퇴 및 하퇴 골절에 로봇시스템을 적용할 경우 하퇴부위에 대해서는 이중의 안전조치와 더불어 견인력 제어분해능을 20 N 간격으로, 대퇴부위에서는 30 N이하의 제어분해능 설정으로 임상에 적용할 수 있을 것으로 판단되었다.
3.3 골절부에 대한 랜덤 제어성능 실험 결과
하퇴 골절 및 대퇴 골절 더미모델에 BMI를 각각 랜덤하게 실험한 측정값의 근사도를 랜덤실험시 측정값과 BMI별 회귀식에 BMI를 대입한 값을 비교함으로써 랜덤 제어성능을 비교하였다. 그 결과, 하퇴 골절더미에 대해 서는 견인력이 줄어들수록 랜덤 제어오차가 증가하는 것으로 나타났으며, 견인력 100 N이하에서는 20% 이상의 제어오차가 발생하였다. 또한 대퇴 골절부에 대해서는 반복 제어성능과 같이 견인력 300 N의 경우를 제외하고는 모든 견인력에서 10% 이상의 제어오차가 나타났으며, 견인력 50 N에서는 반복 제어성능의 최대오차보다 10% 이상 큰 제어오차(31.68%)가 측정되었다. 따라서 반복 제어실험과 마찬가지로 랜덤 제어실험에서도 하퇴 골절 부위보다는 대퇴골절부위에 대한 견인제어가 상대적으로 어려운 것으로 나타났다(Fig. 5). 그러나 랜덤 제어오차에 대한 편차에서는 하퇴 및 대퇴 골절모델에서 견인력의 증감에 따른 큰 영향을 받지 않고 일정한 값을 보였다.
Fig. 5

Approximate rate of the random experiment to the BMI trend line in fractured tibia (up) and femur (down) dummy

KSPE_2019_v36n10_983_f005.jpg
본 연구를 통해 정형외과용 견인로봇시스템의 임상 적용과정에서 필요한 견인력 정보를 확보하고자 인체 더미모델을 통해 다양한 체형과 골절부위를 고려한 실험을 수행하였다. 본 실험을 통해 골절부위에 적용가능한 견인력 정보와 반복 및 랜덤 실험을 통해 제어성능에 대한 평가를 각각 수행하게 되었다.
BMI가 증가함에 따라 하퇴 골절부에 작용하는 부하값은 비례하여 증가하고, 대퇴 골절부에 작용하는 부하는 감소한다는 결과를 고려해 볼 때 골절정복 수술 과정에 로봇시스템을 적용할 수는 있겠지만, 반복제어성능과 랜던제어성능과 관련된 실험에서 예측값과 실험값 간의 오차가 적게는 약 5% 많게는 약 32%까지 넓게 나타나는 것을 감안해 볼 때, 로봇시스템을 통한 견인력 제어를 전적으로 의존하기보다는 보조적인 도구로만 적용하는 것이 보다 적절할 것으로 사료된다. 실제 제어성능 실험과정에서 계산값 대비 측정값이 하퇴 골절부에서는 항상 낮게 나타났으며, 반대로 대퇴 골절부에서는 항상 높게 나타났는데, 이는 인체 더미모델의 거상속도와 이중 안전장치(하드웨어 및 소프트웨어 한계설정)로 기인한 것으로 분석되었고, 임상적용시 수술 보조도구로써의 사용 가능성을 좀더 지지해 주는 결과로 나타났다. 또한 인체 더미모델을 구현하는 과정에서 인체의 길이와 무게를 주요하게 고려하였고, 근육과 건, 그리고 인대 등 연조직에 대한 고려가 이뤄지지 않음으로 인해 실제 인체와의 유사성에 대한 한계가 있어 이에 대한 영향을 고려한 추가연구가 필요할 것으로 사료된다. 그리고 하지를 위주로 확보된 견인력 정보와 제어성능인 것을 감안해 볼 때, 상지부 적용에 대한 확장성을 기대해 볼 수 있겠으나, 임상에서 적용하기에는 여전히 낮은 제어성능으로 판단되는 바 향후 상지부 적용을 위해서는 견인부에 대한 보다 정교한 제어모듈 설계가 필요할 것으로 판단된다.
결론적으로, 본 연구를 통해 하지 골절정복 수술과정에서 견인로봇시스템을 적용하였을 때 BMI별로 골절된 하퇴와 대퇴부위에서의 관절부하를 예측해 보았으며, 골절정복시 적용되는 견인력을 고려해 볼 때 기존의 의료 인력이 수행하던 업무를 로봇이 대신할 수 있는 가능성은 확인할 수 있었다. 또한 보다 정밀한 견인력 제어와 실시간 견인부하 모니터링이 가능해진다면, 향후 보조인력 및 전문 의료인력에 대한 비용적인 부담 및 근골격 상해부담을 감소시킬 수 있는 수술보조기기가 될 수 있을 것으로 사료된다.
This research was supported by Regional Industry Nurturing Program funded by Ministry of Trade, Industry and Energy (A012100009).
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    Joung, S., Liao, H., Kobayashi, E., Mitsuishi, M., Nakajima, Y., et al., “Hazard Analysis of Fracture-Reduction Robot and its Application to Safety Design of Fracture-Reduction Assisting Robotic System,” Proc. of the International Conference on Robotics and Automation, pp. 1554-1561, 2010.
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Tae Soo Bae
KSPE_2019_v36n10_983_bf001.jpg
Associate Professor in the Department of Biomedical Engineering, Jungwon University, South Korea. His research interests include musculoskeletal dynamic analyses, surgical navigation in orthopedic & rehabilitation research, and other physics-based simulations related to medical devices.
Byeong Chan Cho
KSPE_2019_v36n10_983_bf002.jpg
Master Candidate in the Department of Biomedical Engineering, Jungwon University in Korea. His research interest is on the computational mechanics related to dynamic analysis
Jae Woong Han
KSPE_2019_v36n10_983_bf003.jpg
Research Professor in KOREA University Research Institute of Engineering and Technology. His research interest is Mechanical Engineering Design, Motion Analysis and Medical Device.

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Evaluation of Joint Load as Pre-Operative Traction in Fracture Reduction Surgeries of Femur and Tibia
J. Korean Soc. Precis. Eng.. 2019;36(10):983-988.   Published online October 1, 2019
DOI: https://doi.org/10.7736/KSPE.2019.36.10.983
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Evaluation of Joint Load as Pre-Operative Traction in Fracture Reduction Surgeries of Femur and Tibia
J. Korean Soc. Precis. Eng.. 2019;36(10):983-988.   Published online October 1, 2019
DOI: https://doi.org/10.7736/KSPE.2019.36.10.983
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Evaluation of Joint Load as Pre-Operative Traction in Fracture Reduction Surgeries of Femur and Tibia
Image Image Image Image Image
Fig. 1 Assembly of multi-segment dummy including fractured femur and fractured tibia segments
Fig. 2 Experimental setup for traction robot with the dummy model
Fig. 3 Joint forces during each traction force (50-300 N) applied to fractured tibia and fractured femur of the dummy. For each traction force, upper figure showed joint force of fractured tibia and lower figure showed that of fractured femur repectively
Fig. 4 Approximate rate of the repeated experiment to the BMI trend line for fractured tibia (up) and fractured femur (down) dummy
Fig. 5 Approximate rate of the random experiment to the BMI trend line in fractured tibia (up) and femur (down) dummy

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Evaluation of Joint Load as Pre-Operative Traction in Fracture Reduction Surgeries of Femur and Tibia
Under weight Normal weight
Height
(m)		 Weight
(kg)		 BMI
(kg/m2)		 Height
(m)		 Weight
(kg)		 BMI
(kg/m2)
1.63 43 16.18 1.63 52 19.57
1.58 43 17.22 1.73 60 20.05
1.73 52 17.37 1.58 52 20.93
1.53 43 18.37 1.68 60 21.26
1.68 52 18.42 1.53 52 22.21
Over weight Obese weight
Height
(m)		 Weight
(kg)		 BMI
(kg/m2)		 Height
(m)		 Weight
(kg)		 BMI
(kg/m2)
1.93 95 25.50 1.78 95 30.12
1.83 86 25.68 1.93 104 31.05
1.88 95 26.88 1.73 95 31.74
1.78 86 27.14 1.78 104 32.82
1.73 86 28.73 1.73 104 34.75
Group Height (m) Weight (kg) BMI (kg/m2)
Under weight 1.73 52 17.37
Normal weight 1.58 52 20.93
Over weight 1.88 95 26.88
Obese weight 1.73 95 31.74
Fractured tibia dummy Fractured femur dummy
Height
(m)		 Weight
(kg)		 BMI
(kg/m2)		 Height
(m)		 Weight
(kg)		 BMI
(kg/m2)
1.78 52 16.4 1.83 52 15.5
1.93 86 23.1 1.58 60 24.1
1.83 95 28.4 1.53 60 25.6
1.63 86 32.4 1.68 104 36.9
Table 1 Experimental groups according to body mass index
Table 2 Selection of human dummy models for repeated control performance test
Table 3 Selection of human dummy models for random control performance test

Table 1

Table 2

Table 3

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