Design and Evaluation of a Fiber-Optic Grip Force Sensor with Compliant 3D-Printable Structure for (f)MRI Applications

Grip force sensors compatible with magnetic resonance imaging (MRI) are used in human motor control and decision-making research, providing objective and sensitive behavioral outcome measures. Commercial sensors are expensive, cover limited force ranges, rely on pneumatic force transmission that cannot detect fast force changes, or are electrically active, which increases the risk of electromagnetic interference. We present the design and evaluation of a low-cost, 3D-printed, inherently MRI-compatible grip force sensor based on a commercial intensity-based fiber-optic sensor. A compliant monobloc structure with flexible hinges transduces grip force to a linear displacement captured by the fiber-optic sensor. The structure can easily be adapted for different force ranges by changing the hinge thickness. A prototype designed for forces up to 800 N was manufactured and showed a highly linear behavior (nonlinearity of 2.37%) and an accuracy of 1.57% in a range between zero and 500 N. It can be printed and assembled within one day and for less than $300. Accurate performance was confirmed, both inside and outside a 3 T MRI scanner within a pilot study. Given its simple design allowing for customization of sensing properties and ergonomics for different applications and requirements, the proposed grip force handle offers researchers a valuable scientific tool

An observational study to assess validity and reliability of smartphone sensor-based gait and balance assessments in multiple sclerosis: Floodlight GaitLab protocol

Background Gait and balance impairments are often present in people with multiple sclerosis (PwMS) and have a significant impact on quality of life and independence. Gold-standard quantitative tools for assessing gait and balance such as motion capture systems and force plates usually require complex technical setups. Wearable sensors, including those integrated into smartphones, offer a more frequent, convenient, and minimally burdensome assessment of functional disability in a home environment. We developed a novel smartphone sensor-based application (Floodlight) that is being used in multiple research and clinical contexts, but a complete validation of this technology is still lacking. Methods This protocol describes an observational study designed to evaluate the analytical and clinical validity of Floodlight gait and balance tests. Approximately 100 PwMS and 35 healthy controls will perform multiple gait and balance tasks in both laboratory-based and real-world environments in order to explore the following properties: (a) concurrent validity of the Floodlight gait and balance tests against gold-standard assessments; (b) reliability of Floodlight digital measures derived under different controlled gait and balance conditions, and different on-body sensor locations; (c) ecological validity of the tests; and (d) construct validity compared with clinician- and patient-reported assessments. Conclusions The Floodlight GaitLab study (ISRCTN15993728) represents a critical step in the technical validation of Floodlight technology to measure gait and balance in PwMS, and will also allow the development of new test designs and algorithms

Device for a Novel Hand and Wrist Rehabilitation Strategy for Stroke Patients Based on Illusory Movements Induced by Tendon Vibration

This paper presents a new device for a novel neurorehabilitation strategy for stroke patients suffering from upper limb paralysis. The concept consists in combining illusory movements, induced by tendon vibration on the hand and wrist, with a virtual reality visualization of the hand to support the positive effects of motor imagery reported in the literature. The aim is to induce and support plastic processes in affected brain regions to promote the ability to perform basic gestures like grasping. The device is capable of vibrating simultaneously or independently with an adjustable frequency on precise locations on the flexor tendons of the five fingers. The experimental results show that strong illusory movements can be induced in a group of 10 healthy subjects with a very high reliability of 86 to 100% demonstrating the concept feasibility and performance of the solution

Performance metrics for an application-driven selection and optimization of psychophysical sampling procedures

When estimating psychometric functions with sampling procedures, psychophysical assessments should be precise and accurate while being as efficient as possible to reduce assessment duration. The estimation performance of sampling procedures is commonly evaluated in computer simulations for single psychometric functions and reported using metrics as a function of number of trials. However, the estimation performance of a sampling procedure may vary for different psychometric functions. Therefore, the results of these type of evaluations may not be generalizable to a heterogeneous population of interest. In addition, the maximum number of trials is often imposed by time restrictions, especially in clinical applications, making trial-based metrics suboptimal. Hence, the benefit of these simulations to select and tune an ideal sampling procedure for a specific application is limited. We suggest to evaluate the estimation performance of sampling procedures in simulations covering the entire range of psychometric functions found in a population of interest, and propose a comprehensive set of performance metrics for a detailed analysis. To illustrate the information gained from these metrics in an application example, six sampling procedures were evaluated in a computer simulation based on prior knowledge on the population distribution and requirements from proprioceptive assessments. The metrics revealed limitations of the sampling procedures, such as inhomogeneous or systematically decreasing performance depending on the psychometric functions, which can inform the tuning process of a sampling procedure. More advanced metrics allowed directly comparing overall performances of different sampling procedures and select the best-suited sampling procedure for the example application. The proposed analysis metrics can be used for any sampling procedure and the estimation of any parameter of a psychometric function, independent of the shape of the psychometric function and of how such a parameter was estimated. This framework should help to accelerate the development process of psychophysical assessments.ISSN:1932-620

The Lagging Legs Exploiting Body Dynamics to Steer a Quadrupedal Agent

Abstract ⎯ The goal of this work was to steer a quadrupedal agent simply by changing the phase delay between its legs. Thus, we were able to show that a quadrupedal agent could possibly reach every point on a plane simply by exploiting its body dynamics. By exploiting body dynamics the controller has to fulfill only the function of a disturbance variable rather than exactly controlling the parameters of an agent’s movement. I

Enhancing simulations with intra-subject variability for improved psychophysical assessments

Psychometric properties of perceptual assessments, like reliability, depend on stochastic properties of psychophysical sampling procedures resulting in method variability, as well as inter- and intra-subject variability. Method variability is commonly minimized by optimizing sampling procedures through computer simulations. Inter-subject variability is inherent to the population of interest and cannot be influenced. Intra-subject variability introduced by confounds (e.g., inattention or lack of motivation) cannot be simply quantified from experimental data, as these data also include method variability. Therefore, this aspect is generally neglected when developing assessments. Yet, comparing method variability and intra-subject variability could give insights on whether effort should be invested in optimizing the sampling procedure, or in addressing potential confounds instead. We propose a new approach to estimate intra-subject variability of psychometric functions by combining computer simulations and behavioral data, and to account for it when simulating experiments. The approach was illustrated in a real-world scenario of proprioceptive difference threshold assessments. The behavioral study revealed a test-retest reliability of r = 0.212. Computer simulations without considering intra-subject variability predicted a reliability of r = 0.768, whereas the new approach including an intra-subject variability model lead to a realistic estimate of reliability (r = 0.207). Such a model also allows computing the theoretically maximally attainable reliability (r = 0.552) assuming an ideal sampling procedure. Comparing the reliability estimates when exclusively accounting for method variability versus intra-subject variability reveals that intra-subject variability should be reduced by addressing confounds and that only optimizing the sampling procedure may be insufficient to achieve a high reliability. This new approach allows computing the intra-subject variability with only two measurements per subject, and predicting the reliability for a larger number of subjects and retests based on simulations, without requiring additional experiments. Such a tool of predictive value is especially valuable for target populations where time is scarce, e.g., for assessments in clinical settings.ISSN:1932-620

Performance metrics for an application-driven selection and optimization of psychophysical sampling procedures.

When estimating psychometric functions with sampling procedures, psychophysical assessments should be precise and accurate while being as efficient as possible to reduce assessment duration. The estimation performance of sampling procedures is commonly evaluated in computer simulations for single psychometric functions and reported using metrics as a function of number of trials. However, the estimation performance of a sampling procedure may vary for different psychometric functions. Therefore, the results of these type of evaluations may not be generalizable to a heterogeneous population of interest. In addition, the maximum number of trials is often imposed by time restrictions, especially in clinical applications, making trial-based metrics suboptimal. Hence, the benefit of these simulations to select and tune an ideal sampling procedure for a specific application is limited. We suggest to evaluate the estimation performance of sampling procedures in simulations covering the entire range of psychometric functions found in a population of interest, and propose a comprehensive set of performance metrics for a detailed analysis. To illustrate the information gained from these metrics in an application example, six sampling procedures were evaluated in a computer simulation based on prior knowledge on the population distribution and requirements from proprioceptive assessments. The metrics revealed limitations of the sampling procedures, such as inhomogeneous or systematically decreasing performance depending on the psychometric functions, which can inform the tuning process of a sampling procedure. More advanced metrics allowed directly comparing overall performances of different sampling procedures and select the best-suited sampling procedure for the example application. The proposed analysis metrics can be used for any sampling procedure and the estimation of any parameter of a psychometric function, independent of the shape of the psychometric function and of how such a parameter was estimated. This framework should help to accelerate the development process of psychophysical assessments

Enhancing simulations with intra-subject variability for improved psychophysical assessments.

Psychometric properties of perceptual assessments, like reliability, depend on stochastic properties of psychophysical sampling procedures resulting in method variability, as well as inter- and intra-subject variability. Method variability is commonly minimized by optimizing sampling procedures through computer simulations. Inter-subject variability is inherent to the population of interest and cannot be influenced. Intra-subject variability introduced by confounds (e.g., inattention or lack of motivation) cannot be simply quantified from experimental data, as these data also include method variability. Therefore, this aspect is generally neglected when developing assessments. Yet, comparing method variability and intra-subject variability could give insights on whether effort should be invested in optimizing the sampling procedure, or in addressing potential confounds instead. We propose a new approach to estimate intra-subject variability of psychometric functions by combining computer simulations and behavioral data, and to account for it when simulating experiments. The approach was illustrated in a real-world scenario of proprioceptive difference threshold assessments. The behavioral study revealed a test-retest reliability of r = 0.212. Computer simulations without considering intra-subject variability predicted a reliability of r = 0.768, whereas the new approach including an intra-subject variability model lead to a realistic estimate of reliability (r = 0.207). Such a model also allows computing the theoretically maximally attainable reliability (r = 0.552) assuming an ideal sampling procedure. Comparing the reliability estimates when exclusively accounting for method variability versus intra-subject variability reveals that intra-subject variability should be reduced by addressing confounds and that only optimizing the sampling procedure may be insufficient to achieve a high reliability. This new approach allows computing the intra-subject variability with only two measurements per subject, and predicting the reliability for a larger number of subjects and retests based on simulations, without requiring additional experiments. Such a tool of predictive value is especially valuable for target populations where time is scarce, e.g., for assessments in clinical settings

Reliable and Rapid Robotic Assessment of Wrist Proprioception Using a Gauge Position Matching Paradigm

Quantitative assessments of position sense are essential for the investigation of proprioception, as well as for diagnosis, prognosis and treatment planning for patients with somatosensory deficits. Despite the development and use of various paradigms and robotic tools, their clinimetric properties are often poorly evaluated and reported. A proper evaluation of the latter is essential to compare results between different studies and to identify the influence of possible confounds on outcome measures. The aim of the present study was to perform a comprehensive evaluation of a rapid robotic assessment of wrist proprioception using a passive gauge position matching task. Thirty-two healthy subjects undertook six test-retests of proprioception of the right wrist on two different days. The constant error (CE) was 0.87°, the absolute error (AE) was 5.87°, the variable error (VE) was 4.59° and the total variability (E) was 6.83° in average for the angles presented in the range from 10° to 30°. The intraclass correlation analysis provided an excellent reliability for CE (0.75), good reliability for AE (0.68) and E (0.68), and fair reliability for VE (0.54). Tripling the assessment length had negligible effects on the reliabilities. Additional analysis revealed significant trends of larger overestimation (constant errors), as well as larger absolute and variable errors with increased flexion angles. No proprioceptive learning occurred, despite increased familiarity with the task, which was reflected in significantly decreased assessment duration by 30%. In conclusion, the proposed automated assessment can provide sensitive and reliable information on proprioceptive function of the wrist with an administration time of around 2.5 min, demonstrating the potential for its application in research or clinical settings. Moreover, this study highlights the importance of reporting the complete set of errors (CE, AE, VE, and E) in a matching experiment for the identification of trends and subsequent interpretation of results