Micro machined tactile sensor for soft tissue compliance detection

Purpose This study aimed to develop a quantitative dry cupping system that can monitor negative pressure attenuation and soft tissue pull-up during cupping to quantify soft tissue compliance. Methods Baseball players with myofascial pain syndrome were recruited to validate the benefits of cupping therapy. Nine of 40 baseball players on the same team were diagnosed with trapezius myofascial pain syndrome; another nine players from the same team were recruited as controls. All participants received cupping with a negative pressure of 400 mmHg for 15 minutes each time, twice a week, for 4 weeks. Subjective perception was investigated using upper extremity function questionnaires, and soft tissue compliance was quantified objectively by the system. Results During the 15-minute cupping procedure, pressure attenuation in the normal group was significantly greater than that in the myofascial group (p = 0.017). The soft tissue compliance in the normal group was significantly higher than that in the myofascial group (p = 0.050). Moreover, a 4-week cupping intervention resulted in an obvious increase in soft tissue lift in the myofascial pain group (p = 0.027), although there was no statistical difference in the improvement of soft tissue compliance. Shoulder (p = 0.023) and upper extremity function (p = 0.008) were significantly improved in both groups, but there was no significant difference between the two groups. Conclusion This quantitative cupping monitoring system could immediately assess tissue compliance and facilitate the improvement of soft tissues after cupping therapy. Hence, it can be used in athletes to improve their functional recovery and maintain soft tissues health during the off-season period.

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Clinical Use of Tissue Compliance Meter for Documentation of Soft Tissue Pathology

Clinical Journal of Pain ◽

10.1097/00002508-198703010-00005 ◽

1987 ◽

Vol 3 (1) ◽

pp. 23-30 ◽

Cited By ~ 37

Author(s):

Andrew A. Fischer

Keyword(s):

Soft Tissue ◽

Clinical Use ◽

Tissue Compliance

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Computed Tomography in Deep Venous Thrombosis with Limb Oedema

Acta Radiologica Diagnosis ◽

10.1177/028418518502600617 ◽

1985 ◽

Vol 26 (6) ◽

pp. 727-730 ◽

Cited By ~ 7

Author(s):

E. Seem ◽

E. Stranden ◽

M. G. Stiris

Keyword(s):

Computed Tomography ◽

Hydrostatic Pressure ◽

Soft Tissue ◽

Venous Thrombosis ◽

Deep Venous Thrombosis ◽

Interstitial Fluid ◽

Lower Limbs ◽

Compartment Syndromes ◽

Tissue Compliance ◽

Tissue Compartments

Computed tomography was used in 12 patients to investigate the distribution of oedema in the soft tissue compartments of lower limbs with deep venous thrombosis. Oedema was evenly distributed throughout the subcutis and the muscular compartments in tomograms obtained 25 cm proximal to the ankle. Significantly less swelling in the muscular compartments was found 10 cm proximal to the ankle. Interstitial fluid hydrostatic pressure was measured in the subcutis, and in anterior and posterior muscular compartments, and was significantly increased in all cases. Except for one case, the recorded pressures were well below 30 mmHg, which is considered the limit above which compartment syndromes occur. Tissue compliance was significantly lower in muscular compartments than in the subcutis.

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Measuring Soft Tissue Compliance of the Human Thigh

10.4271/2004-01-2158 ◽

2004 ◽

Cited By ~ 2

Author(s):

Jürgen Hartung ◽

Christian Mergl ◽

Christian Henneke ◽

Ramon Madrid-Dusik ◽

Heiner Bubb

Keyword(s):

Soft Tissue ◽

Tissue Compliance

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Spinal soft tissue compliance in juvenile chronic arthritis by vacuum

Physiotherapy Theory and Practice ◽

10.3109/09593989509022397 ◽

1995 ◽

Vol 11 (1) ◽

pp. 45-50 ◽

Cited By ~ 1

Author(s):

Jorn A. Hogeweg ◽

Rob A.B. Oostendorp ◽

Paul J.M. Helders

Keyword(s):

Soft Tissue ◽

Juvenile Chronic Arthritis ◽

Chronic Arthritis ◽

Tissue Compliance

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Design, Modeling and Simulation of a Micro Tactile Sensor for Soft Tissue Stiffness Measurement with Three Tips Configuration

2015 Seventh International Conference on Computational Intelligence, Modelling and Simulation (CIMSim) ◽

10.1109/cimsim.2015.28 ◽

2015 ◽

Cited By ~ 1

Author(s):

Ahmed Fouly ◽

Mohamed N. A. Nasr ◽

Ahmed M. R. Fath El Bab ◽

A. A. Abouelsoud

Keyword(s):

Soft Tissue ◽

Modeling And Simulation ◽

Tactile Sensor ◽

Tissue Stiffness ◽

Stiffness Measurement

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Design and Simulation of Micro Tactile Sensor for Stiffness Detection of Soft Tissue with Irregular Surface

Sensor Letters ◽

10.1166/sl.2020.4207 ◽

2020 ◽

Vol 18 (3) ◽

pp. 200-209

Author(s):

Ahmed Fouly ◽

Ahmed M. R. FathEl-Bab ◽

A. A. Abouelsoud ◽

T. Tsuchiya ◽

O. Tabata

Keyword(s):

Soft Tissue ◽

Soft Tissues ◽

Tactile Sensor ◽

Sensor Output ◽

Irregular Surface ◽

Tissue Stiffness ◽

Tactile Sensors ◽

Element Analysis ◽

Detailed Design ◽

Sensor Structure

Tactile sensors become an essential part of many applications in our life. Integrating tactile sensors with surgical tools used in MIS is significant to compensate for the shortage of touch feeling of soft tissues and organs comparing with traditional surgeries. This paper presents a detailed design of a micro tactile sensor for measuring the stiffness of soft tissue with an irregular surface. The sensor consists of five cantilever springs with different stiffness. A spring in the middle has a relatively low stiffness surrounded by 4 springs have relatively equal high stiffness to compensate for the soft tissue contact error in the longitudinal and lateral directions. Sensor parameters are selected to ensure high sensitivity and linearity with taking into consideration the cross-talk effect among the sensor springs tips. A detailed design of the sensor structure in the microscale is conducted based on some constraints related to MEMS fabrication. A finite element analysis (FEA) of the sensor structure is conducted to evaluate sensor structure performance using CoventorWare software. Then, an FEA for the piezo-resistors, as a signal transduction method, is conducted which maps the sensor output to an electrical signal. The results prove that the sensor can differentiate among different soft-tissue stiffness within the selected range independent of the applied distance between the sensor and the tissue with an error below 3% even with inclination angle between the sensor and the tissue ±3°. Furthermore, a linear performance has been achieved between the soft-tissue stiffness and the sensor output.

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