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. An alternative strategy involves the implementation of an iPhone application that enables the device to serve as a functional wireless accelerometer system. The Parkinson's disease tremor attributes may be recorded in either an effectively autonomous public or private setting, for which the resultant accelerometer signal of the tremor can be conveyed wireless and through email to a remote location for data post-processing. The initial testing and evaluation of the iPhone wireless accelerometer application for quantifying Parkinson's disease tremor successfully demonstrates the capacity to acquire tremor characteristics in an effectively autonomous environment, while potentially alleviating strain on limited and highly specialized medical resources.

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. The acquired gait cycle data was transmitted wireless and through email for subsequent post-processing in a location remote to the location where the experiment was conducted. The iPhone application functioning as a wireless accelerometer for the acquisition of gait characteristics has demonstrated sufficient accuracy and consistency.

Accelerometers have become increasingly integrated in the biomedical field, as they are highly portable and capable of objectively and reliably quantifying motion. Two specific applications for accelerometers are the quantification of gait and movement disorders, such as Parkinson's disease and essential tremor. The evolution of accelerometers to their present status is discussed. Accelerometry is contrasted with more traditional means for accessing gait and movement disorders. Advances in the research validation of accelerometers for the characterization of gait and movement disorders, such as essential tremor and Parkinson's disease, are addressed. The review concludes with the advancement of three-dimensional (3D) wireless accelerometers and pertinent future implications.

The deep tendon reflex is a fundamental aspect of a neurological examination. The two major parameters of the tendon reflex are response and latency, which are presently evaluated qualitatively during a neurological examination. The reflex loop is capable of providing insight into the status and therapy response of both upper and lower motor neuron syndromes. Attempts have been made to ascertain reflex response and latency; however, these systems are relatively complex, resource intensive, with issues of consistent and reliable accuracy. The solution presented is a wireless quantified reflex device using tandem three-dimensional (3D) wireless accelerometers to obtain response based on acceleration waveform amplitude and latency derived from temporal acceleration waveform disparity. Three specific aims have been established for the proposed wireless quantified reflex device: (1) Demonstrate the wireless quantified reflex device is reliably capable of ascertaining quantified reflex response and latency using a quantified input. (2) Evaluate the precision of the device using an artificial reflex system. (3) Conduct a longitudinal study respective of subjects with healthy patellar tendon reflexes, using the wireless quantified reflex evaluation device to obtain quantified reflex response and latency. Aim 1 has led to a steady evolution of the wireless quantified reflex device from a singular 2D wireless accelerometer capable of measuring reflex response to a tandem 3D wireless accelerometer capable of reliably measuring reflex response and latency. The hypothesis for aim 1 is that a reflex quantification device can be established for reliably measuring reflex response and latency for the patellar tendon reflex, comprised of an integrated system of wireless 3D MEMS accelerometers. Aim 2 further emphasized the reliability of the wireless quantified reflex device by evaluating an artificial reflex system. The hypothesis for aim 2 is that the wireless quantified reflex device can obtain reliable reflex parameters (response and latency) from an artificial reflex device. Aim 3 synthesizes the findings relevant to aim 1 and 2, while applying the wireless accelerometer reflex quantification device to a longitudinal study of healthy patellar tendon reflexes. The hypothesis for aim 3 is that during a longitudinal evaluation of the deep tendon reflex the parameters for reflex response and latency can be measured with a considerable degree of accuracy, reliability, and reproducibility. Enclosed is a detailed description of a wireless quantified reflex device with research findings and potential utility of the system, inclusive of a comprehensive description of tendon reflexes, prior reflex quantification systems, and correlated applications.

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