Rebecca D Butler

US Patent:

20200375695, Dec 3, 2020

Filed:

Mar 8, 2018

Appl. No.:

16/491567

Inventors:

- Hanover NH, US
Rebecca BUTLER - Hanover NH, US
Michael SALIN - Lower Gwynedd PA, US

International Classification:

A61C 5/44
A61C 8/00
A61B 17/16

Abstract:

A dental drill system with electrical-impedance sensing indicates when a bit of the drill system approaches cortical-cancellous bone, or bone-soft tissue interfaces. The drill system has a dental drill handset having a cannula bearing electrically coupled to a drilling bit, the drilling bit having an electrically insulated portion and an exposed portion. The cannula bearing is coupled to an electrical impedance spectroscopy sensing device configured to measure impedance between the cannula bearing of the dental drill handset and a ground plate, and a processing system uses EIS measurements to distinguish when the bit of the drill system approaches cortical- or cancellous bone, or bone-soft tissue interfaces.

US Patent:

20170196497, Jul 13, 2017

Filed:

Jan 6, 2017

Appl. No.:

15/400789

Inventors:

- Hanover NH, US
Harrison King Hall - Hanover NH, US
Jim Lever - Lebanon NH, US
Susan Taylor - Lebanon NH, US
Erik Kobylarz - Lyme NH, US
Erfan Azad - Hanover NH, US
Dvij Bajpai - Hanover NH, US
Rebecca Butler - Hanover NH, US
Latika Sridhar - Hanover NH, US

International Classification:

A61B 5/00
G06N 99/00
A61B 7/04
A61B 5/0205
A61B 5/0402
A61B 5/0488
G06F 19/00
A61B 3/113

Abstract:

A system and method for identifying ictal states in a patient, the system including a plurality of sensors for sensing different non-electroencephalographic signals from the patient, and a processing unit. The processing unit has a processor and memory with instructions for classifying data from the plurality of sensors to determine probability of the patient being ictal, when the probability is high asking the patient if the patient is in an ictal state, reporting to a caregivers if the patient is ictal, and updating the classifier based upon sensor data, probability, and the response. The method includes sensing, using a plurality of non-electroencephalographic sensors, determining, using a classifier trained using a training dataset, probability of the patient being in an ictal state, and if probability is high, asking the patient if the patient is in ictal state, logging the occurrence of an ictal state, and updating the classifier.