Surgery – Diagnostic testing – Detecting muscle electrical signal
Reexamination Certificate
2001-02-23
2003-03-11
Hindenburg, Max F. (Department: 3736)
Surgery
Diagnostic testing
Detecting muscle electrical signal
C600S540000
Reexamination Certificate
active
06532383
ABSTRACT:
BACKGROUND OF THE INVENTION
This invention relates to the detection and processing of rapidly changing bioelectric or other signals. More particularly, it relates to methods for detecting, processing smoothing signals having rapidly changing amplitudes, such as EMG signals, which may be generated by the tongue or other muscles, and for providing stable and discrete output signals from input signals detected by a detector, such as an intraoral device.
The use of electromyographic (EMG) signals for control of a prosthesis was proposed by Reiter in 1948. In 1958, an actual surface EMG or myoelectrically controlled prosthetic hand was introduced in Russia. EMG signals recorded from remaining agonist and antagonist muscles in the residual limb of a transradial amputee were used. Since the 1960's, the use of myoelectric control of prostheses and orthoses has continued to be studied and successfully implemented. There are now myoelectric prosthetic devices which use surface EMG signals recorded from one or two muscle sites for proportional or digital actuation of one or more functions of an electric powered prosthetic component.
During the late 1960's and early 1970's, electromyographic or myoelectric based control strategies were studied and compared with myomechanical position controllers. The use of surface EMG or myoelectric controllers has been limited by the long integration intervals required to stabilize rapidly fluctuating surface EMG signals. These long integration intervals slow down the responsivity of the controller. A second limitation of myoelectric controllers has been the small number of resolvable discrete control signal levels obtainable (approximately five). Myomechanical position controlling systems have been found to provide a greater number of discrete control levels, as well as more stable control signals.
A myomechanical technique has been developed for use with mid-cervical spinal cord injured individuals using shoulder movement transduction for proportional two-axis control of prosthetic and orthotic systems, including systems employing functional electrical stimulation. Limitations in using shoulder movement transduction for proportional two-axis control of orthotic and neuroprosthetic systems in the high quadriplegic include a) a decrease in the number of discrete control signal levels achievable and a decrease in the stability of the control signals as the level of spinal cord injury become higher, b) control signal interference from motion of the contralateral shoulder, c) instability of reference position due to postural changes and attachment methods of the position transduce, and d) difficulty in concealing the transducer. Recently there has been renewed interest in using processed surface EMG or myoelectric signals as control signals in spinal cord injured individuals in a single dimensional functional electrical stimulation task.
Oral motor and sensory impairments, including dysphagia and dysarthria, can result from many causes including: traumatic brain injury, cerebral palsy, stroke and other diseases of the nervous system such as Parkinson's disease, multiple sclerosis and amyotrophic lateral sclerosis. The occurrence of oral motor and sensory dysfunction increases with age and can result in increased difficulty with communication, decline in nutritional status and, in some cases, aspiration pneumonia. Improved methods for measuring intraoral motor and sensory function are needed.
Electromyographic (EMG) signals from the genioglossus muscle have been previously measured using surface electrodes placed over the skin under the mandible and using surface electrodes mounted to mandibular appliances or splints. With previous intraoral EMG recording techniques, two to four electrodes are used. Electrode wires exit the mouth anteriorly between the upper and lower incisors and hinder approximation of the teeth.
The mounting of two surface electrodes 3 mm in diameter to the palate side of a maxillary splint has been described by Schwarts, et al. Used to stimulate the soft palate, these electrodes were located 1 cm apart, centered to midline, and 2-3 cm posterior to the vibrating line on the soft palate. The methods by which the two electrode wires exited the mouth was not described.
U.S. Pat. No. 5,212,476 invented by Sean R. Maloney describes an intraoral device for detecting EMG signals from the tongue. The Maloney device describes a single splint having a convex side which may be in contact with either the maxillary or mandibular and includes active electrodes mounted on the splint adjacent to the tongue.
OBJECTS OF THE INVENTION
It is therefore one object of the invention to provide an improved method for smoothing input signals having rapidly changing amplitudes.
It is another object of the invention to provide an improved method for converting EMG signals generated from the tongue to signals having stable and discrete levels.
It is still another object of the invention to provide an improved intraoral device for detecting EMG signals from the tongue.
SUMMARY OF THE INVENTION
One aspect of this invention calls for digital processing techniques which can smooth and stabilize a bioelectric of other signal amplitude and an integrated (with respect to time) bioelectric or other integrated signal amplitude which change rapidly in an irregular or random (stochastic) fashion due to the asynchronous nature of the constituent or contributing components of the signal or integrated signal amplitude. The fluctuatory signal amplitude to be processed can be a unipolar (+ or −) or a bipolar (+ and −) signal amplitude. Examples of bipolar bioelectric signal amplitudes which can be processed using the techniques include electromyographic (EMG) or myoelectric, electroneurographic (ENG) or nerve, and electroencephalographic (EEG) or brain signal amplitudes.
These signal processing techniques decrease signal or integrated signal amplitude variability (i.e., smooth the signal or integrated signal amplitude) using an adaptive moving average process and an exponential average process while maintaining signal or integrated signal amplitude responsiveness (i.e., adequate rate of signal or integrated signal amplitude change for a given application). The signal or integrated signal amplitude is stabilized by converting the smoothed but still fluctuating signal or integrated signal amplitude into a discrete signal, or integrated signal, amplitude using an interactive variable windowing process. Smoothing the varying signal or integrated signal amplitude prior to forming a discrete or stable signal or integrated signal amplitude increases the number of resolvable signal or integrated signal amplitude values. Using this signal or integrated signal amplitude stabilizing technique allows the discrete signal or integrated signal value to be maintained for a time interval suitable for the digital signal processing application.
One potential application for these digital signal processing techniques is the conversion of a fluctuating surface electromyographic (EMG) signal amplitude or integrated surface EMG signal amplitude into a processed myoelectric, signal or integrated signal, amplitude to control orthotic (brace), prosthetic (artificial limb), neuroprosthetic (prosthesis which uses limb functional electrical stimulation), robotics, and other (external) devices.
A second application for these digital signal processing techniques is the conversion of a bioelectric or other randomly changing signal, or integrated signal, amplitude into a series of discrete signal amplitudes or discrete integrated signal amplitudes for signal or integrated signal amplitude measurement purposes. These techniques allow resolution of the processed signal amplitude or integrated signal amplitude into discrete time and discrete signal amplitude or integrated signal amplitude domains. For example, rectified EMG or integrated EMG signal amplitudes could be processed into smoothed and stabilized discrete amplitude or integrated amplitude values. These discrete val
Maloney Sean R.
Shoaf Sarah C.
Zlotolow Ian M.
Carter & Schnedler, P.A.
Hindenburg Max F.
Wingood Pamela L.
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