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

Objective assessment of spasticity by pendulum test: a systematic review on methods of implementation and outcome measures

Background

Instrumented pendulum test is an objective and repeatable biomechanical method of assessment for spasticity. However, multitude of sensor technologies and plenty of suggested outcome measures, confuse those interested in implementing this method in practice. Lack of a standard agreement on the definition of experimental setup and outcome measures adds to this ambiguity and causes the results of one study not to be directly attainable by a group that uses a different setup. In this systematic review of studies, we aim to reduce the confusion by providing pros and cons of the available choices, and also by standardizing the definitions.

Methods

A literature search was conducted for the period of 1950 to the end of 2019 on PubMed, Science Direct, Google Scholar and IEEE explore; with keywords of “pendulum test” and “Spasticity”.

Results

Twenty-eight studies with instrumented pendulum test for assessment of spasticity met the inclusion criteria. All the suggested methods of implementation were compared and advantages and disadvantages were provided for each sensor technology. An exhaustive list categorized outcome measures in three groups of angle-based, angular velocity-based, and angular acceleration-based measures with all different names and definitions.

Conclusions

With the aim of providing standardized methodology with replicable and comparable results, sources of dissimilarity and ambiguity among research strategies were found and explained with the help of graphical representation of pendulum movement stages and corresponding parameters on the angular waveforms. We hope using the provided tables simplify the choices when implementing pendulum test for spasticity evaluation, improve the consistency when reporting the results, and disambiguate inconsistency in the literature.

Classification and Assessment of the Patelar Reflex Response through Biomechanical Measures

Clinical evaluation of the patellar reflex is one of the most frequent diagnostic methods used by physicians and medical specialists. However, this test is usually elicited and diagnosed manually. In this work, we develop a device specifically designed to induce the patellar reflex and measure the angle and angular velocity of the leg during the course of the reflex test. We have recorded the response of 106 volunteers with the aim of finding a recognizable pattern in the responses that can allow us to classify each reflex according to the scale of the National Institute of Neurological Disorders and Stroke (NINDS). In order to elicit the patellar reflex, a hammer is attached to a specially designed pendulum, with a controlled impact force. All volunteer test subjects sit at a specific height, performing the Jendrassik maneuver during the test, and the medical staff evaluates the response in accordance with the NINDS scale. The data acquisition system is integrated by using a tapping sensor, an inertial measurement unit, a control unit, and a graphical user interface (GUI). The GUI displays the sensor behavior in real time. The sample rate is 5 kHz, and the control unit is configured for a continuous sample mode. The measured signals are processed and filtered to reduce high-frequency noise and digitally stored. After analyzing the signals, several domain-specific features are proposed to allow us to differentiate between various NINDS groups using machine learning classifiers. The results show that it is possible to automatically classify the patellar reflex into a NINDS scale using the proposed biomechanical measurements and features.

Validity and reliability of smartphone applications for clinical assessment of the neuromusculoskeletal system

INTRODUCTION

Clinicians increasingly use smartphone medical applications. There is no evidence to support the validity and reliability of applications used to assess the neuromusculoskeletal system. The aim of this study was to systematically review the quality of studies as well as the validity and reliability of using a smartphone as a clinical assessment tool for the neuromusculoskeletal system. Areas covered: PubMed, CINAHL and Embase were searched. A manual search was also conducted. Additionally, forward snowballing of relevant articles was performed in Scopus and Web of Science. Two reviewers independently selected the articles, extracted the data using a standardized form and assessed the articles quality based on a scoring system Expert commentary: Thirty-four articles were found eligible and were categorized into four groups: Range of Motion (ROM), posture and deformity, tremors and reflexes, and gait and mobility. Only the ROM category supported the validity and reliability of using smartphone applications as assessment tools. Regarding quality assessment scores, the articles in ROM and posture and deformity categories ranged from poor to good quality, whereas those in the tremors and reflexes and gait and mobility categories had poor quality.

Joint position sense - There׳s an app for that

Traditionally, proprioception has been assessed with a passive model, in which an external apparatus moves a body segment. Recently, protocols have been developed based on active movements, which are more representative of functional activities. However, even these approaches require expensive testing equipment and the necessity of a visit to a research lab, as there are no commercially available mobile instruments that allow for the assessment of proprioception outside of a laboratory setting. The objective of this study was to demonstrate the validity and feasibility of using a mobile device (iPod Touch) to assess joint position. We conducted a concurrent validity study in the lab (n=9) and a field based study (n=79). The field based study was conducted at the 2012 American Society of Biomechanics meeting in Gainesville, Florida. The results of both studies demonstrate good agreement with our established protocol using a magnetic tracking device, with angular errors decreasing with increasing shoulder flexion angles. The studies demonstrate the validity and feasibility of using mobile devices for assessing motion-based parameters, both inside and outside of a laboratory setting.

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. However, the reliability of the ordinal scale approach is debatable. Highly skilled clinicians have even disputed the presence of asymmetric reflex pairs. An alternative strategy was the implementation of an iPod wireless accelerometer application to quantify the reflex response acceleration waveform. An application enabled the recording of the acceleration waveform and later wireless transmission as an email attachment by connectivity to the Internet. A potential energy impact pendulum enabled the patellar tendon reflex to be evoked in a predetermined and targeted manner. Three feature categories of the reflex response acceleration waveform (global parameters, temporal organization, and spectral features) were incorporated into machine learning to distinguish a subject's hemiplegic and healthy reflex pair. Machine learning attained perfect classification of the hemiplegic and healthy reflex pair. The research findings implicate the promise of machine learning for providing increased diagnostic acuity regarding the acceleration waveform of the tendon reflex response.

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. The quantification of the tendon reflex response has been successfully demonstrated with considerable accuracy and consistency through using a potential energy impact pendulum attached to a reflex hammer for evoking the tendon reflex with a smartphone, such as an iPhone, application representing a wireless accelerometer platform to quantify reflex response. Another sensor integrated into the smartphone, such as an iPhone, is the gyroscope, which measures rate of angular rotation. A smartphone application enables wireless transmission through Internet connectivity of the gyroscope signal recording of the reflex response as an email attachment. The smartphone wireless gyroscope application demonstrates considerable accuracy and consistency for the quantification of the tendon reflex response.

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. The objective of the research was to demonstrate the capacity of the smartphone to quantify gait features of a trans-tibial prosthesis. The iPhone a standard smartphone was mounted to the carbon fiber blade of the prosthesis through an adapter developed by a 3D printer. The application demonstrated considerable accuracy and reliability for the quantification of gait characteristics.

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. The implication of such devices as a wireless accelerometer platform is the experimental and post-processing locations can be placed anywhere in the world. Gait was quantified by mounting a smartphone or portable media device proximal to the lateral malleolus of the ankle joint. Attributes of the gait cycle were quantified with a considerable accuracy and reliability. The patellar tendon reflex response was quantified by using the device in tandem with a potential energy impact pendulum to evoke the patellar tendon reflex. The acceleration waveform maximum acceleration feature of the reflex response displayed considerable accuracy and reliability. By mounting the smartphone or portable media device to the dorsum of the hand through a glove, Parkinson's disease hand tremor was quantified and contrasted with significance to a non-Parkinson's disease steady hand control. With the methods advocated in this chapter, any aspect of human movement may be quantified through smartphones or portable media devices and post-processed anywhere in the world. These wearable devices are anticipated to substantially impact the biomedical and healthcare industry.