Chinese folk instrument identification based on pitch histogram

2014 ◽  
Author(s):  
Weiwei Zhang ◽  
Junxing Zhang ◽  
Jianjun He
Keyword(s):  
Instrument Identification

Feasibility of opto-electronic surgical instrument identification

2009 ◽  
Vol 18 (5) ◽  
pp. 253-258 ◽  
Author(s):  
Michael Kranzfelder ◽  
Armin Schneider ◽  
Gerhard Blahusch ◽  
Hansgeorg Schaaf ◽  
Hubertus Feussner
Keyword(s):  
Surgical Instrument ◽  
Instrument Identification

scholarly journals Assessing the efficacy of tablet-based simulations for learning pseudo-surgical instrumentation

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0245330
Author(s):  
James H. Kryklywy ◽  
Victoria A. Roach ◽  
Rebecca M. Todd
Keyword(s):  
Real World ◽  
Response Times ◽  
Learning Task ◽  
Identification Accuracy ◽  
Training Methods ◽  
Perioperative Nurses ◽  
Surgical Instrumentation ◽  
Educational Environments ◽  
Performance Decline ◽  
Instrument Identification

Nurses and surgeons must identify and handle specialized instruments with high temporal and spatial precision. It is crucial that they are trained effectively. Traditional training methods include supervised practices and text-based study, which may expose patients to undue risk during practice procedures and lack motor/haptic training respectively. Tablet-based simulations have been proposed to mediate some of these limitations. We implemented a learning task that simulates surgical instrumentation nomenclature encountered by novice perioperative nurses. Learning was assessed following training in three distinct conditions: tablet-based simulations, text-based study, and real-world practice. Immediately following a 30-minute training period, instrument identification was performed with comparable accuracy and response times following tablet-based versus text-based training, with both being inferior to real-world practice. Following a week without practice, response times were equivalent between real-world and tablet-based practice. While tablet-based training does not achieve equivalent results in instrument identification accuracy as real-world practice, more practice repetitions in simulated environments may help reduce performance decline. This project has established a technological framework to assess how we can implement simulated educational environments in a maximally beneficial manner.

scholarly journals P.102 Simulation-based training for surgical instrument recognition

2017 ◽  
Vol 44 (S2) ◽  
pp. S39-S40
Author(s):  
DB Clarke ◽  
M Hong ◽  
N Kureshi ◽  
L Fenerty ◽  
G Thibault-Halman ◽  
...  
Keyword(s):  
Simulation Training ◽  
Surgical Simulation ◽  
Surgical Instruments ◽  
Perioperative Nurses ◽  
Instrument Recognition ◽  
Simulation Based ◽  
Group A ◽  
Repeated Use ◽  
Instrument Identification ◽  
Group B

Background: Surgical simulation training offers trainees the opportunity to practice surgical skills before entering the operating room. The objectives of this study were to determine the effect of simulation for learning instruments for burr hole surgery and whether this learning is translated to real instrument recognition with retention. Methods: Randomized trials of PGY1 neurosurgery residents and perioperative nurses were conducted, using PeriopSim™ for instrument recognition, as well as real instruments. Group A performed simulation tasks using PeriopSim™ prior to identifying real instruments, whereas Group B identified real instruments prior to performing simulation tasks. Nurses’ recall was assessed at seven days. Results: Sixteen residents and 100 nurses were recruited. All participants showed significant overall improvement in their scores for simulated tasks. Group A demonstrated enhanced accuracy and speed of identifying real instruments compared with Group B (p<0.001). Furthermore, knowledge recall testing at one week demonstrated retained learning, shown by 97% accuracy in instrument identification. Conclusions: Our results demonstrate that recognition of surgical instruments improves with repeated use of the PeriopSim™ platform. Instrument knowledge acquired through simulation training results in improved identification and retained recognition of real instruments.

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