TissueDB/Simulators/Knot Tying Force-Feedback Simulator (Amiel)
The Knot Tying Force-Feedback Simulator (Amiel) ("Knoti") is a bench-top force-feedback device for practising one-handed square-knot tying for vessel ligation.[1] A force sensor measures reaction force while the learner ties a knot inside a plexiglass tube that creates a deep working field. The feedback unit changes its visual and audible signal at 1.3 N. This value is derived from expert knot-tying performance and is not a measured tissue-damage, vessel-avulsion, suture-breakage, or knot-failure threshold.
| Field | Details |
|---|---|
| Features and Basic Operation | The device has four principal functional components: a hook on which the knot is tied; a plexiglass tube that creates a deep surgical working field; a force sensor connected to a computer by USB; and a feedback unit with green/red visual signals and audible alarms. Below the 1.3 N expert-performance threshold, the system provides a green light and intermittent beep. Above the threshold, it provides a red light and persistent beep. The software records force-related measures and knot-completion time. |
| Current Development Status | The original force-measurement device was reported by Laufer et al. in 2016.[2] A subsequent construct-validity study compared 15 experienced surgeons with 30 surgery residents and established the expert force-performance distinction used for the later feedback threshold.[3] Amiel et al. (2020) then reported a training benefit in 14 PGY-1 and PGY-2 surgical residents using force feedback. Operating-room skills transfer or patient-outcome benefit was not demonstrated. |
| Estimated Build Time and Cost | - - |
| Specialized Tools and Equipment | A personal computer is required for data logging and receives sensor data over USB. The system also requires the force sensor, feedback electronics, visual indicators, audible alarm and associated software. Laufer et al. (2016) is the original hardware source; Amiel et al. (2020) does not provide sufficient sensor specifications, circuit schematics or software specifications for independent reconstruction. Use-time consumables in the 2020 study included 3-0 silk suture and surgical gloves; the study used Sofsilk 3-0 (Medtronic). |
| Version | Version 1 — device lineage reported by Laufer et al. (2016), followed by construct-validity work published online in 2019 and the force-feedback training study reported by Amiel et al. (2020). No later hardware design iteration is established here. |
| Development Team Contact Information | Imri Amiel, Roi Anteby, Moti Cordoba, Shlomi Laufer, Chaya Shwaartz, Danny Rosin, Mordechai Gutman, Amitai Ziv and Roy Mashiach — Faculty of Medicine, Tel Aviv University; Sheba Medical Center, Tel-Hashomer, Ramat-Gan; Israel Center for Medical Simulation (MSR); and Technion – Israel Institute of Technology, Haifa. Corresponding author for the 2020 study: Roi Anteby (roianteby@mail.tau.ac.il). First author: Imri Amiel (imri.amiel@sheba.health.gov.il). |
Structural Parts
| Part Name | Qty | Material | Cost | Notes |
|---|---|---|---|---|
| Hook — component A | 1 | Material not specified in source | - | Task interface on which the learner ties the knot. It represents the location of a vessel-ligation task but is not assigned a TissueDB anatomy target. Material and dimensions are not specified in Amiel et al. (2020). |
| Plexiglass tube — component B | 1 | Plexiglass | - | Creates the constrained deep working field. The top of the tube is positioned 3 cm above the top of the hook. Amiel et al. (2020) does not state the tube diameter, wall thickness or overall length. |
| Force/data sensor — component C | 1 | Not specified in source | - | Measures reaction force at the knot-tying interface and connects to the computer through USB. Amiel et al. (2020) does not specify the sensor model, sensing technology, force range or sampling rate. |
| Feedback unit — component D | 1 | Green and red indicators with audible alarm circuitry | - | Provides real-time feedback relative to the 1.3 N expert-performance threshold. Below the threshold the learner receives a green light and intermittent beep; above it the learner receives a red light and persistent beep. The source does not establish 1.3 N as a material- or tissue-failure threshold. |
| Base / mounting platform | 1 | Material not specified in source | - | Supports the hook, tube, sensor and feedback assembly. It is visible in the published device figure, but its material and dimensions are not reported in Amiel et al. (2020). |
| Computer connection | 1 | USB connection | - | Transfers sensor measurements to the personal computer used for logging and feedback. |
Consumables
| Consumable | Quantity | Material | Approximate Cost | Notes |
|---|---|---|---|---|
| Knot-tying suture | As required per training session | 3-0 silk suture | - | Use-time knot-tying material. Amiel et al. (2020) used Sofsilk 3-0. It is a training consumable and does not create an anatomy relationship. |
| Surgical gloves | 1 pair per learner/session as required | Surgical gloves | - | Use-time consumable reported in the training context. Not part of the permanent Knoti hardware. |
Build Instructions
Source limitation
The available studies describe the Knoti device and its use but do not provide a complete reproducible construction protocol. Laufer et al. (2016) is the original device-hardware source. Amiel et al. (2020) is a force-feedback training study and must not be treated as a complete fabrication manual.
The following section therefore records the documented device configuration. It does not claim to provide sufficient information to manufacture the electronics, sensor system or software.
Documented device configuration
Component A — hook
- Provide the hook used as the knot-tying interface.
- The source available for this page does not state its material or dimensions.
Component B — plexiglass tube
- Position a plexiglass tube around/over the hook to create the deep working field.
- The top of the tube is 3 cm above the top of the hook.
- Tube diameter, length and wall thickness are not specified in Amiel et al. (2020).
Component C — force sensor
- The system includes a sensor that measures reaction force at the knot-tying interface.
- Connect the sensor to a personal computer by USB.
- Sensor type, range, sampling rate and detailed mounting configuration are not specified in Amiel et al. (2020).
Component D — feedback unit
- The feedback unit includes green and red visual indicators and an audible alarm.
- Configure the feedback logic around the 1.3 N expert-performance threshold described by the study.
- Below 1.3 N: green visual signal and intermittent beep.
- Above 1.3 N: red visual signal and persistent beep.
- The available source does not provide a circuit schematic or sufficient electronic specification to reproduce the feedback unit independently.
Base
- Mount the device components on a stable platform.
- The published figure shows the mounting arrangement, but Amiel et al. (2020) does not state the platform material or dimensions.
Training setup and documented function
- Connect the force sensor to the computer through USB.
- Run the associated data-logging and feedback software.
- Use 3-0 silk suture for the one-handed square-knot task.
- Tie the knot on the hook while working through the plexiglass depth constraint.
- The system measures the force generated during the task.
- The feedback unit provides the green/intermittent signal below the 1.3 N expert-performance threshold and the red/persistent signal above it.
- The software records total-force information, peak pulling force, peak pushing force and knot-completion time.
Evidence note: these feedback states describe documented device behaviour. They are not a TissueDB fabrication QA specification.
Scope and limitations
- Force direction: the system measures the vertical-axis reaction force described by the source; it is not a multi-axis force-measurement system.
- Threshold meaning: 1.3 N is derived from expert performance. It is not a measured vessel-avulsion, tissue-tear, thread-breakage or knot-failure threshold.
- Knot integrity: knot quality in the study was evaluated visually rather than by tensile failure testing.
- Training population: the 2020 feedback-training study enrolled 14 PGY-1 and PGY-2 surgical residents.
- Clinical transfer: operating-room skills transfer was not demonstrated by the 2020 study.
- Reproducibility: sensor specifications, electronic schematics and software specifications are insufficiently reported on this page for independent reconstruction of the system.
| Alternative names | Knoti; KNOTI |
|---|
| Authors | Arturopelayo |
|---|---|
| License | CC-BY-SA-4.0 |
| Cite as | Arturopelayo (2026). "TissueDB/Simulators/Knot Tying Force-Feedback Simulator (Amiel)". Appropedia. Retrieved September 12, 2026. |
- ↑ Amiel I, Anteby R, Cordoba M, Laufer S, Shwaartz C, Rosin D, Gutman M, Ziv A, Mashiach R. "Feedback based simulator training reduces superfluous forces exerted by novice residents practicing knot tying for vessel ligation." American Journal of Surgery. 2020;220(1):100–104. DOI: 10.1016/j.amjsurg.2019.11.027. PMID: 31806168.
- ↑ Laufer S, Amiel I, Nathwani JN, Mashiach R, Margalit RS, Ray RD, Ziv A, Pugh CM. "A Simulator for Measuring Forces During Surgical Knots." Studies in Health Technology and Informatics. 2016;220:199–204. PMID: 27046578.
- ↑ Amiel I, Anteby R, Cordoba M, Laufer S, Shwaartz C, Rosin D, Gutman M, Ziv A, Mashiach R. "Experienced surgeons versus novice surgery residents: validating a novel knot tying simulator for vessel ligation." Surgery. 2020;167(4):699–703; first published online 2 November 2019. DOI: 10.1016/j.surg.2019.09.017. PMID: 31685234.