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Dove Medical Press

New method for identifying abnormal milling states of an otological drill

Overview of attention for article published in Medical Devices : Evidence and Research, May 2015
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Title
New method for identifying abnormal milling states of an otological drill
Published in
Medical Devices : Evidence and Research, May 2015
DOI 10.2147/mder.s77313
Pubmed ID
Authors

Yunqing Li, Xisheng Li, Guodong Feng, Zhiqiang Gao, Peng Shen

Abstract

Surgeons are continuing to strive toward achieving higher quality minimally invasive surgery. With the growth of modern technology, intelligent medical devices are being used to improve the safety of surgery. Milling beyond the bone tissue wall is a common abnormal milling state in ear surgery, as well as entanglement of the drill bit with the cotton swab, which will do harm to the patient's encephalic tissues. Various methods have been investigated by engineers and surgeons in an effort to avoid this type of abnormal milling state during surgery. This paper outlines a new method for identifying these two types of abnormal milling states. Five surgeons were invited to perform experiments on calvarial bones. The average recognition rate for otological drill milling through a bone tissue wall was 93%, with only 2% of normal millings being incorrectly identified as milling faults. The average recognition rate for entanglement of the drill bit with a cotton swab was 92%, with only 2% of normal millings being identified as milling faults. The method presented here can be adapted to the needs of the individual surgeon and reliably identify milling faults.

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X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 2 20%
Student > Master 2 20%
Other 1 10%
Unspecified 1 10%
Student > Bachelor 1 10%
Other 3 30%
Readers by discipline Count As %
Engineering 5 50%
Computer Science 1 10%
Unspecified 1 10%
Medicine and Dentistry 1 10%
Energy 1 10%
Other 0 0%
Unknown 1 10%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 June 2015.
All research outputs
#16,106,935
of 25,457,858 outputs
Outputs from Medical Devices : Evidence and Research
#173
of 314 outputs
Outputs of similar age
#150,504
of 279,098 outputs
Outputs of similar age from Medical Devices : Evidence and Research
#6
of 8 outputs
Altmetric has tracked 25,457,858 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 314 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.3. This one is in the 41st percentile – i.e., 41% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 279,098 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.