A System for Characterizing Intraoperative Force Distribution During Operative Laryngoscopy.
Journal
IEEE transactions on bio-medical engineering
ISSN: 1558-2531
Titre abrégé: IEEE Trans Biomed Eng
Pays: United States
ID NLM: 0012737
Informations de publication
Date de publication:
09 2020
09 2020
Historique:
pubmed:
25
1
2020
medline:
25
6
2021
entrez:
25
1
2020
Statut:
ppublish
Résumé
This study aimed to create and validate an integrated data acquisition system for gauging the force distribution between a laryngoscope and soft-tissue during trans-oral surgery. Sixteen piezoresistive force sensors were interfaced to a laryngoscope and custom maxillary tooth guard. A protocol for calibrating the laryngoscope and maxilla sensors was developed using a motor-controlled linear stage and force measurements were validated against a digital scale. The system was initially tested during suspension laryngoscopy on three cadaver heads mounted on a cadaver head-holder. Intraoperative data was also collected from three patients undergoing head and neck tumor resection. Mean calibration error of the scope sensors was less than 150 g (n = 3) and mean maxilla sensor error was less than 200 g (n = 3). Peak scope mag-forces of 8.09 ± 6.61 kg and peak maxilla forces of 7.62 ± 4.57 kg were experienced during the cadaver trials. The peak scope sensor mag-force recorded during the intraoperative cases was 24.7 ± 4.53 kg, and the peak maxilla force was 22.0 ± 4.60 kg. The data acquisition system was successfully able to record intraoperative force distribution data. The usefulness of this technology in informing surgeons during trans-oral surgery should be further evaluated in patients with varying anatomic and procedural characteristics. Creation of a low-cost, integrated force-sensing system allows for the characterization of retraction forces at anatomic sites including the pharynx and larynx, brain, and abdomen. Real-time force detection provides surgeons with valuable intraoperative feedback and can be used to improve deformation models at various anatomic sites.
Identifiants
pubmed: 31976874
doi: 10.1109/TBME.2020.2966954
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM