Showing papers by "Sebastian Fudickar published in 2018"

Towards an Automated Unsupervised Mobility Assessment for Older People Based on Inertial TUG Measurements

Abstract: One of the most common assessments for the mobility of older people is the Timed Up and Go test (TUG). Due to its sensitivity regarding the indication of Parkinson's disease (PD) or increased fall risk in elderly people, this assessment test becomes increasingly relevant, should be automated and should become applicable for unsupervised self-assessments to enable regular examinations of the functional status. With Inertial Measurement Units (IMU) being well suited for automated analyses, we evaluate an IMU-based analysis-system, which automatically detects the TUG execution via machine learning and calculates the test duration. as well as the duration of its single components. The complete TUG was classified with an accuracy of 96% via a rule-based model in a study with 157 participants aged over 70 years. A comparison between the TUG durations determined by IMU and criterion standard measurements (stopwatch and automated/ambient TUG (aTUG) system) showed significant correlations of 0.97 and 0.99, respectively. The classification of the instrumented TUG (iTUG)-components achieved accuracies over 96%, as well. Additionally, the system's suitability for self-assessments was investigated within a semi-unsupervised situation where a similar movement sequence to the TUG was executed. This preliminary analysis confirmed that the self-selected speed correlates moderately with the speed in the test situation, but differed significantly from each other.

Counteracting the Slowdown of Reaction Times in a Vigilance Experiment With 40-Hz Transcranial Alternating Current Stimulation

Abstract: Indicators for a decrement in vigilance are a slowdown in reaction times and an increase in alpha power in the electroencephalogram in posterior regions of the brain. Transcranial alternating current stimulation (tACS) is a neuropsychological technique that has been found to interact with intrinsic brain oscillations and is able to enhance cognitive and behavioral performance. Recent studies show that tACS in the gamma frequency range (30–80 Hz) is able to downregulate amplitudes in the alpha frequency range (8–12 Hz), in accordance to the effect referred to as cross-frequency coupling, where intrinsic alpha and gamma waves modulate each other. We applied 40 Hz gamma-tACS to the visual cortex during a vigilance experiment and investigated if stimulation improves reaction times and error rates with time-on-task. In our sham controlled experiment, participants completed two blocks of 30 minutes duration while performing the same visual two-choice task. The first block was used as BASELINE. A statistical analysis with a linear mixed model revealed a significantly lower increase of modeled reaction times over time in the INTERVENTION-block of the tACS-group as compared with their BASELINE-block whereas there was no significant change between the BASELINE- and INTERVENTION-block for the SHAM-group. Error rates did not differ between groups. This paper indicates that gamma-tACS can enhance performance in vigilance tasks as it significantly decreased the slowdown of reaction times in our study.

Scanning Laser Rangefinders for the Unobtrusive Monitoring of Gait Parameters in Unsupervised Settings.

Abstract: Since variations in common gait parameters (such as cadence, velocity and stride-length) of elderly people are a reliable indicator of functional and cognitive decline in aging and increased fall risks, such gait parameters have to be monitored continuously to enable preventive interventions as early as possible. With scanning laser rangefinders (SLR) having been shown to be suitable for standardised (frontal) gait assessments, this article introduces an unobtrusive gait monitoring (UGMO) system for lateral gait monitoring in homes for the elderly. The system has been evaluated in comparison to a GAITRite (as reference system) with 86 participants (ranging from 21 to 82 years) passing the 6-min walk test twice. Within the considered 56,351 steps within an overall 7877 walks and approximately 34 km distance travelled, it has been shown that the SLR Hokuyo UST10-LX is more sensitive than the cheaper URG-04LX version in regard to the correct (automatic) detection of lateral steps (98% compared to 77%) and walks (97% compared to 66%). Furthermore, it has been confirmed that the UGMO (with the SLR UST10-LX) can measure gait parameters such as gait velocity and stride length with sufficient sensitivity to determine age- and disease-related functional (and cognitive) decline.

Stair Climb Power Measurements via Inertial Measurement Units - Towards an Unsupervised Assessment of Strength in Domestic Environments.

Abstract: In order to initiate interventions at an early stage of functional decline and thus, to extend independent living, the early detection of changes in functional ability is important. The Stair Climb Power Test (SCPT) is a standard test in geriatric assessments for strength as one of the essential components of functional ability. This test is also well suited for regular and frequent power measurements in daily life since the activity of climbing stairs is usually frequently performed. We introduce an automated assessment of the SCPT based on inertial measurement units (IMU) in a study of 83 participants aged 70-87 years. For power evaluations of the lower extremities, the activity of climbing stairs was automatically classified via machine learning and the power was calculated based on the test duration and covered height. Climbing stairs was correctly classified in 93% of the cases. We also achieved a good correlation of the power calculations with the conventional stop watch measurements with a mean deviation of 2.35%. The system’s sensitivity to detect the transition towards frailty has been confirmed. Furthermore, we discussed the general suitability of the automated stair climb power algorithm in unsupervised, standardized

A Wearable Vibrotactile Interface for Unfavorable Posture Awareness Warning

Abstract: We present the concept of a vibrotactile interface with up to 13 tactors (vibration motors) that are distributed over the full body to warn industry workers when taking unfavorable postures. The developed system is to be integrated into a motion capture workwear for industry workers to serve as posture feedback system to prevent unfavorable or even harmful postures. Such postures are a risk factor for musculoskeletal disorders (MSD), especially among older adults. We evaluated the vibrotactile system with 11 subjects to identify the optimal notification vibration sequences (regarding pulse length and repetition) and the accuracy of the location-dependent perception. Results indicate that the optimal pulse length is about 150 ms and is repeated 2 or 3 times within the sequence for maximum attention.

Determining Cardiopulmonary Resuscitation Parameters with Differential Evolution Optimization of Sinusoidal Curves.

Abstract: In this paper, we present a robust sinusoidal curve fitting method based on the Differential Evolution (DE) algorithm for determining cardiopulmonary resuscitation (CPR) parameters – naming chest compression frequency and depth – from skeletal motion data. Our implementation uses skeletal data from the RGB-D (RGB + Depth) Kinect v2 sensor and works without putting non-sensor related constraints such as specific view angles or distance to the system. Our approach is intended to be part of a robust and easy-to-use feedback system for CPR training, allowing its unsupervised training. We compare the sensitivity of our DE implementation with data recorded by a Laerdal Resusci Anne mannequin. Results show that the frequency of the DE-based CPR is recognized with a variance of ±4.4 bpm (4.1%) in comparison to the reference of the Resusci Anne mannequin.

Evaluation of Power-Based Stair Climb Performance via Inertial Measurement Units

Abstract: The stair climbing test (SCT) is a standard geriatric assessment to measure lower-limb strength being one of the essential components of physical function. To detect functional decline as early as possible, regular assessments of mobility, balance, and strength are necessary. Inertial measurement units (IMU) are a promising technology for flexible and unobtrusive measurements of the SCTs. We introduce an automated assessment via IMUs in a study of 83 participants aged 70–87 (75.64 ± 4,17) years. The activity of stair ascending has been automatically classified via a k-nearest-neighbor classifier and the performance was evaluated regarding the power. Therefore, we considered both, stair climb average power and peak power. Stair ascending was correctly classified in 93% of the cases with a mean deviation of 2.35% of the average power value in comparison to conventional measurements. Additionally, we showed the medical sensitivity of our system regarding the detection of transitions towards the frail status in controlled conditions and also confirmed the general suitability of automated stair climb analyses in unsupervised home-assessments.

Development of a Mobile Functional Near-infrared Spectroscopy Prototype and its Initial Evaluation: Lessons Learned

Abstract: This paper presents a new mobile near-infrared functional spectroscopy (fNIRS) device, with digital detectors that can be placed anywhere on the head and fit into standard caps to measure cortical brain activation. The device's functionality was evaluated in two steps, i.e. first, by means of simple pulse measurements and second, in a motor cortex study with nine subjects. In this study, the subjects had to alternate between right and left hands while using hand-held strength trainers. While the signals from the mobile prototype were not yet stable enough across all channels to perform analysis such as statistical parametric mapping, it was able to measure significant brain activation changes over the area of the motor cortex with the mobile prototype when the contralateral hand was activated in four subjects. In contrast, the device was yet unable to measure ipsilateral activities. The problems encountered and possible methods to improve signal acquisition are discussed at the end of the paper.

Staying Alive - CPR Quality Parameters from Wrist-worn Inertial Sensor Data with Evolutionary Fitted Sinusoidal Models

Abstract: In this paper, a robust sinusoidal model fitting method based on the Differential Evolution (DE) algorithm for determining cardiopulmonary resuscitation (CPR) quality-parameters - naming chest compression frequency and depth - as measured by an inertial sensor placed at the wrist is presented. Once included into a smartphone or smartwatch app, the proposed algorithm will enable bystanders to improve CPR (as part of a continuous closed-loop support-system). By evaluating the precision of the model with data recorded by a Laerdal Resusci Anne mannequin as reference standard, a low variance for compression frequency of $\pm 2.0$ cpm has been found for the sensor placed at the wrist, making this previously unconsidered position a suitable alternative to the typical placement in the hand for CPR-training smartphone apps.

Development of a Mobile Functional Near-Infrared Spectroscopy Prototype

Abstract: Driving is a complex and cognitively demanding task. It is important to assess the cognitive state of the driver in order to develop cognitive technical systems that can adapt to different cognitive states of the driver. For this purpose, we have developed a mobile functional near-infrared spectroscopy (mofNIRS) prototype. This paper describes the improvements of this mobile prototype with freely placeable optodes on a subject’s head and the results of an evaluation study. We conducted a motor cortex experiment with four subjects, whereby the mobile prototype was mounted on the right hemisphere and a commercial, stationary fNIRS on the left hemisphere above the motor cortex area. One data set had to be discarded due to incorrect synchronization between both systems. The results of the remaining three subjects are presented and discussed in this paper. Here, we report the results from the time-series and Statistical Parametric Mapping (SPM) analyses, which shows t-values with high differentiability of the Results. Furthermore, both analysis methods show comparable results between the commercial system and the mobile prototype.

XML Skeleton Definitions for Human Posture Assessments.

Abstract: In this paper, we show how the XML dialect SKAML (Skeletal Assessment Markup Language) can be used to use data from one or more Motion Capture systems to perform human posture assessments with multiple assessment methods. We show an implementation example using an inertial measuring suit and both OWAS and REBA assessment methods. SKAML makes it possible to implement classifiers for a Motion Capture system once and adapt the classifier by-configuration to various ergonomics assessment methods. We anticipate our work as help for researchers and developers that implement new assessment methods or motion capture systems.