Multi-device patient ambulation system

Abstract

Various embodiments of an ambulation and movement assist system are disclosed. For example, an ambulation system for a patient may comprise an exoskeleton device attached to the patient, an FES device at least partially implanted in the patient, and a biological interface apparatus. The biological interface apparatus comprises a sensor having a plurality of electrodes for detecting multicellular signals, a processing unit configured to receive the multicellular signals from the sensor, process the multicellular signals to produce a processed signal, and transmit the processed signal to a controlled device. At least one of the exoskeleton device and the FES device is the controlled device of the biological interface apparatus.

Description

[0001] This application claims the benefit of priority under 35 U.S.C. § 119(e) of U.S. Provisional Application No. 60 / 641,986, filed Jan. 6, 2005. This application relates to commonly assigned U.S. application Ser. No. ______ of J. Christopher Flaherty et al., entitled “NEURALLY CONTROLLED PATIENT AMBULATION SYSTEM” and filed on the same date as the present application. The complete subject matter of the above-referenced applications is incorporated by reference herein.FIELD OF THE INVENTION [0002] The present invention relates to medical devices and related methods. More particularly, various embodiments relate to ambulation and movement assist systems. The systems may include a biological interface apparatus and a movement assist apparatus, such as an ambulation assist apparatus. The biological interface apparatus may include one or more devices controlled by processed multicellular signals of a patient. A processing unit produces a control signal based on multicellular signals r...

AI Technical Summary

Benefits of technology

[0008] In an embodiment, the controlled device is an apparatus to assist in the movement of one or more limbs of the patient such as an exoskeleton device or a Functional Electrical Stimulation (FES) device. Ambulation assist apparatus may consist of a patient walker, a cane, a scooter, a wheelchair, or other device applicable to a patient with impaired motor function such as a paraplegic or quadriplegic patient. One or more sensors in the ambulation assist apparatus produces data signals that can be used by the system to improve performance and safety, as well as detect a potentially dangerous situation such as a condition in which the patient has fallen. Data can be transferred from the ambulation assist apparatus to the biological interface apparatus with wired or wireless means.

[0010] In an embodiment, the controlled device and / or the movement assist apparatus is an exoskeleton device or a FES device. One or more sensors in the movement assist apparatus produces data signals that can be used by the system to improve performance and safety, as well as detect a potentially dangerous situation such as a condition in which the patient has fallen. Data can be transferred from the movement assist apparatus to the biological interface apparatus with wired or wireless means.

[0012] In an embodiment, the controlled device and / or the movement assist apparatus is an exoskeleton device or a FES device. One or more sensors in the movement assist apparatus produces data signals that can be used by the system to improve performance and safety, as well as detect a potentially dangerous situation such as a condition in which the patient has fallen. Data can be transferred from the movement assist apparatus to the biological interface apparatus with wired or wireless means.

Problems solved by technology

Early attempts to utilize signals directly from neurons to control an external prosthesis encountered a number of technical difficulties.

The ability to identify and obtain stable electrical signals of adequate amplitude was a major issue.

Another problem that has been encountered is caused by the changes that occur to the neural signals that occur over time, resulting in a degradation of system performance.

Neural interface systems that utilize other neural information or other neural data, such as electrocorticogram (ECoG) signals, local field potentials (LFPs) and electroencephalogram (EEG) signals have similar issues to those associated with individual neuron signals.

Since all of these signals result from the activation of large groups of neurons, the specificity and resolution of the control signal that can be obtained is limited.

Commercialization of these neural interfaces has been extremely limited, with the majority of advances made by universities in a preclinical research setting.

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