Parametric evaluation of deep brain stimulation parameter configurations for Parkinson's disease using a conformal wearable and wireless inertial sensor system and machine learning.

Deep brain stimulation enables highly specified patient-unique therapeutic intervention ameliorating the symptoms of Parkinson's disease. Inherent to the efficacy of deep brain stimulation is the acquisition of an optimal parameter configuration. Using conventional methods, the optimization process for tuning the deep brain stimulation system parameters can intrinsically induce strain on clinical resources.

Virtual Proprioception for eccentric training.

Wireless inertial sensors enable quantified feedback, which can be applied to evaluate the efficacy of therapy and rehabilitation. In particular eccentric training promotes a beneficial rehabilitation and strength training strategy. Virtual Proprioception for eccentric training applies real-time feedback from a wireless gyroscope platform enabled through a software application for a smartphone.

Wireless gyroscope platform enabled by a portable media device for quantifying wobble board therapy.

The wobble board enables a therapy strategy for rehabilitation of the ankle foot complex. Quantification of therapy, such as through the use of a wobble board, can facilitate a therapist's acuity for advancing and optimizing the overall therapy strategy. The portable media device, such as an iPod, can be equipped with a software application to function as a wireless gyroscope platform.

Implementation of a smartphone as a wireless gyroscope platform for quantifying reduced arm swing in hemiplegie gait with machine learning classification by multilayer perceptron neural network.

Natural gait consists of synchronous and rhythmic patterns for both the lower and upper limb. People with hemiplegia can experience reduced arm swing, which can negatively impact the quality of gait. Wearable and wireless sensors, such as through a smartphone, have demonstrated the ability to quantify various features of gait.

Implementation of a smartphone wireless accelerometer platform for establishing deep brain stimulation treatment efficacy of essential tremor with machine learning.

Essential tremor (ET) is a highly prevalent movement disorder. Patients with ET exhibit a complex progressive and disabling tremor, and medical management often fails. Deep brain stimulation (DBS) has been successfully applied to this disorder, however there has been no quantifiable way to measure tremor severity or treatment efficacy in this patient population.

Implementation of machine learning for classifying prosthesis type through conventional gait analysis.

Current forecasts imply a significant increase in the quantity of lower limb amputations. Synergizing the capabilities of a conventional gait analysis system and machine learning facilitates the capacity to classify disparate types of transtibial prostheses. Automated classification of prosthesis type may eventually advance rehabilitative acuity for selecting an appropriate prosthesis for a given aspect of the rehabilitation process.

Implementation of an iPod wireless accelerometer application using machine learning to classify disparity of hemiplegic and healthy patellar tendon reflex pair.

The characteristics of the patellar tendon reflex provide fundamental insight regarding the diagnosis of neurological status. Based on the features of the tendon reflex response, a clinician may establish preliminary perspective regarding the global condition of the nervous system. Current techniques for quantifying the observations of the reflex response involve the application of ordinal scales, requiring the expertise of a highly skilled clinician.

Use of smartphones and portable media devices for quantifying human movement characteristics of gait, tendon reflex response, and Parkinson's disease hand tremor.

Smartphones and portable media devices are both equipped with sensor components, such as accelerometers. A software application enables these devices to function as a robust wireless accelerometer platform. The recorded accelerometer waveform can be transmitted wireless as an e-mail attachment through connectivity to the Internet.

Implementation of a smartphone for evaluating gait characteristics of a trans-tibial prosthesis.

Smartphone applications have been demonstrated for their capacity to measure gait in functionally autonomous environments beyond the limitations of a traditional gait laboratory. A software application enables the iPhone to function as a wireless accelerometer platform. The recorded acceleration of gait can be transmitted wirelessly as an email attachment through Internet connectivity.

Implementation of a smartphone as a wireless gyroscope application for the quantification of reflex response.

The patellar tendon reflex constitutes a fundamental aspect of the conventional neurological evaluation. Dysfunctional characteristics of the reflex response can augment the diagnostic acuity of a clinician for subsequent referral to more advanced medical resources. The capacity to quantify the reflex response while alleviating the growing strain on specialized medical resources is a topic of interest.

Implementation of an iPhone wireless accelerometer application for the quantification of reflex response.

The patellar tendon reflex represents an inherent aspect of the standard neurological evaluation. The features of the reflex response provide initial perspective regarding the status of the nervous system. An iPhone wireless accelerometer application integrated with a potential energy impact pendulum attached to a reflex hammer has been successfully developed, tested, and evaluated for quantifying the patellar tendon reflex.

Quantified reflex strategy using an iPod as a wireless accelerometer application.

A primary aspect of a neurological evaluation is the deep tendon reflex, frequently observed through the patellar tendon reflex. The reflex response provides preliminary insight as to the status of the nervous system. A quantified reflex strategy has been developed, tested, and evaluated though the use of an iPod as a wireless accelerometer application integrated with a potential energy device to evoke the patellar tendon reflex.

Wireless accelerometer iPod application for quantifying gait characteristics.

The capability to quantify gait characteristics through a wireless accelerometer iPod application in an effectively autonomous environment may alleviate the progressive strain on highly specific medical resources. The iPod consists of the inherent attributes imperative for robust gait quantification, such as a three dimensional accelerometer, data storage, flexible software, and the capacity for wireless transmission of the gait data through email. Based on the synthesis of the integral components of the iPod, a wireless accelerometer iPod application for quantifying gait characteristics has been tested and evaluated in an essentially autonomous environment.

Implementation of an iPhone as a wireless accelerometer for quantifying gait characteristics.

The capacity to quantify and evaluate gait beyond the general confines of a clinical environment under effectively autonomous conditions may alleviate rampant strain on limited and highly specialized medical resources. An iPhone consists of a three dimensional accelerometer subsystem with highly robust and scalable software applications. With the synthesis of the integral iPhone features, an iPhone application, which constitutes a wireless accelerometer system for gait quantification and analysis, has been tested and evaluated in an autonomous environment.

Implementation of an iPhone for characterizing Parkinson's disease tremor through a wireless accelerometer application.

Parkinson's disease represents a chronic movement disorder, which is generally proportionally to age. The status of Parkinson's disease is traditionally classified through ordinal scale strategies, such as the Unified Parkinson's Disease Rating Scale. However, the application of the ordinal scale strategy inherently requires highly specialized and limited medical resources for interpretation.

Wireless accelerometer reflex quantification system characterizing response and latency.

The evaluation of the deep tendon reflex is a standard aspect of a neurological evaluation, which is frequently evoked through the patellar tendon reflex. Important features of the reflex are response and latency, providing insight to status for peripheral neuropathy and upper motor neuron syndrome. A wireless accelerometer reflex quantification system has been developed, tested, and evaluated.

Virtual proprioception with real-time step detection and processing.

Virtual proprioception is a novel device for providing near autonomous biofeedback of hemiparetic gait disparity in real time. With virtual proprioception a user may modify gait dynamics to develop a more suitable gait in tandem with real time feedback. Accelerometers are fundamental to the operation of the device, and a thorough consideration of the accelerometry technology space for locomotion quantification is included.