Werner L. Popp

BACKGROUND Basal ganglia (BG) dysfunction is the hallmark of several neurological and neuropsychiatric disorders. BG dysfunction impairs cost-benefit decision-making, a brain computational process of trading off between reward and costs, and may underlie clinical observations of neuropsychiatric symptoms such as amotivation, impulsivity, and risk-taking. There is an unmet need for a remote digital monitoring tool for cost-benefit decision-making that can be administered repeatedly by a patient at home to provide a longitudinal proxy of basal ganglia functioning to inform clinical practice and drug development efforts. OBJECTIVE This report describes a data-driven and iterative prototyping effort of a smartphone-based, cost-benefit, decision-making test battery developed to measure basal ganglia functioning in three cost domains: effort, delay, and risk. Via an iterative process consisting of multiple rounds of data collection with online community-based samples, we aimed to establish feasibility, proof-of-concept, test-retest reliability over up to 4.5 months, and convergent validity with relevant clinical symptoms, namely apathy and impulsivity. METHODS We converted a lab-based, decision-making test battery to a URL-based test administered on private smartphones. An online pool of n = 879 volunteers aged 40-80 years participated. Using a data-driven approach, we iteratively (6 rounds) refined and shortened the test to a prototype with a target participant burden of less than 5 minutes while preserving its psychometric properties. Proof of concept, test-retest reliability (intraclass correlation coefficients (ICCs)), and convergent validity with the Starkstein Apathy Scale (SAS) and Barrat Impulsiveness Scale (BIS-11) were established for the final version. RESULTS Consistent monotonic effects of cost levels in all cost domains were observed, demonstrating proof of concept. Measures of motivation, impulsivity, and risk-taking showed good to excellent test-retest reliability (ICCs 0.69 – 0.97). Metrics of impulsivity showed convergent validity with its clinical anchor, BIS-11 (t = -2.83, p = 0.005)), and the metric of motivation showed convergent validity with SAS (t = -2.29, p = 0.022). CONCLUSIONS This accessible, short, scalable, and replicable digital smartphone-based decision-making test battery may represent an efficient and robust means to estimate cost-benefit decision-making associated with basal ganglia functioning and its changes over time. CLINICALTRIAL This is not a RCT

We explored the interdependence between wrist and fingers by assessing the influence of wrist posture and external stabilization on precision grip force generation. We found that maximum precision grip force occurred at an extended wrist posture and was 20% greater when the wrist was Externally Stabilized. The latter resulted from amplification of muscle activation patterns from the Self-Stabilized condition rather than adoption of new patterns exploiting external wrist stabilization.

Stochastic stimulation has been shown to improve movement, balance, the sense of touch, and may also improve position sense. This stimulation can be non-invasive and may be a simple technology to enhance proprioception. In this study, we investigated whether sub-threshold stochastic tactile stimulation of mechanoreceptors reduces age-related errors in wrist position estimation. Fifteen young (24.5 +/- 1.5 y and 23 elderly (71.7 +/- 7.3 y) unimpaired, right-handed adults completed a wrist position gauge-matching experiment. In each trial, the participant's concealed wrist was moved to a target position between 10° and 30° of wrist flexion or extension by a robotic manipulandum. The participant then estimated the wrist's position on a virtual gauge. During half of the trials, sub-threshold stochastic tactile stimulation was applied to the wrist muscle tendon areas. Stochastic stimulation did not significantly influence wrist position sense. In the elderly group, estimation errors decreased non-significantly when stimulation was applied compared to the trials without stimulation (mean constant error reduction Dm=0.8° in flexion and Dm=0.7° in extension direction, p=0.95). This effect was less pronounced in the young group (Dm=0.2° in flexion and in extension direction, p=0.99). However, these improvements did not yield a relevant effect size (Cohen's d<0.1). Estimation errors increased with target angle magnitude in both movement directions. In young participants, estimation errors were non-symmetric, with estimations in flexion (mu=1.8°, sd=7.0°) being significantly more accurate than in extension (mu=8.3°, sd=9.3°, p<0.01). This asymmetry was not present in the elderly group, where estimations in flexion (mu=7.5°, sd=9.8°) were similar to extension (mu=7.7°, sd=9.3°). Hence, young and elderly participants performed equally in extension direction, whereas wrist position sense in flexion direction deteriorated with age (p<0.01). Though unimpaired elderly adults did not benefit from stochastic stimulation, it cannot be deduced that individuals with more severe impairments of their sensory system do not profit from this treatment. While the errors in estimating wrist position are symmetric in flexion and extension in elderly adults, young adults are more accurate when estimating wrist flexion, an effect that has not been described before.

Inappropriate physical inactivity is a global health problem increasing the risk of cardiometabolic diseases. Wearable sensors show great potential to promote physical activity and thus a healthier lifestyle. While commercial activity trackers are available to estimate energy expenditure (EE) in non-disabled individuals, they are not designed for reliable assessments in individuals with an incomplete spinal cord injury (iSCI). Furthermore, activity recommendations for this population are currently rather vague and not tailored to their individual needs, and activity guidelines provided for the non-disabled population may not be easily translated for this population. However, especially in iSCI individuals with impaired abilities to stand and walk, the assessment of physical activities and appropriate recommendations for a healthy lifestyle are challenging. Therefore, the study aimed at developing an EE estimation model for iSCI individuals able to walk based on wearable sensor data. Additionally, the data collected within this study was used to translate common activity recommendations for the non-disabled population to easily understandable activity goals for ambulatory individuals with an iSCI. In total, 30 ambulatory individuals with an iSCI were equipped with wearable sensors while performing 12 different physical activities. EE was measured continuously and demographic and anthropometric variables, clinical assessment scores as well as wearable-sensor-derived features were used to develop different EE estimation models. The best EE estimation model comprised the estimation of resting EE using the updated Harris-Benedict equation, classifying activities using a k-nearest neighbor algorithm, and applying a multiple linear regression-based EE estimation model for each activity class. The mean absolute estimation error of this model was 15.2 ± 6.3% and the corresponding mean signed error was −3.4 ± 8.9%. Translating activity recommendations of global health institutions, we suggest a minimum of 2,000–3,000 steps per day for ambulatory individuals with an iSCI. If ambulatory individuals with an iSCI targeted the popular 10,000 steps a day recommendation for the non-disabled population, their equivalent would be around 8,000 steps a day. The combination of the presented dedicated EE estimation model for ambulatory individuals with an iSCI and the translated activity recommendations is an important step toward promoting an active lifestyle in this population.

Background: Cardiovascular diseases are the leading causes of death worldwide, and coronary artery disease (CAD) is one of the most common causes of death in Europe. Leading cardiac societies recommend exercise as an integral part of cardiovascular rehabilitation because it reduces the morbidity and mortality of patients with CAD. Continuous low-intensity exercise using shortening muscle actions (concentric, CON) is a common training modality during cardiovascular rehabilitation. However, a growing clinical interest has been recently developed in high-intensity interval training (HIIT) for stable patients with CAD. Exercise performed with lengthening muscle actions (eccentric, ECC) could be tolerated better by patients with CAD as they can be performed with higher loads and lower metabolic cost than CON exercise. Objective: We developed a clinical protocol on a soft robot to compare cardiovascular and muscle effects of repeated and work-matched CON versus ECC pedaling-type interval exercise between patients with CAD during cardiovascular rehabilitation. This study aims to ascertain whether the developed training protocols affect peak oxygen uptake (VO2peak), peak aerobic power output (Ppeak), and parameters of muscle oxygen saturation (SmO2) during exercise, and anaerobic muscle power. Methods: We will randomize 20-30 subjects to either the CON or ECC group. Both groups will perform a ramp test to exhaustion before and after the training period to measure cardiovascular parameters and SmO2. Moreover, the aerobic skeletal muscle power (Ppeak) is measured weekly during the 8-week training period using a simulated squat jump and a counter movement jump on the soft robot and used to adjust the training load. The pedaling-type interval exercise on the soft robot is performed involving either CON or ECC muscle actions. The soft robotic device being used is a closed kinetic chain, force-controlled interactive training, and testing device for the lower extremities, which consists of two independent pedals and free footplates that are operated by pneumatic artificial muscles. Results: The first patients with CAD, who completed the training, showed protocol-specific improvements, reflecting, in part, the lower aerobic training status of the patient completing the CON protocol. Rehabilitation under the CON protocol, more than under the ECC protocol, improved cardiovascular parameters, that is, VO2peak (+26% vs −6%), and Ppeak (+20% vs 0%), and exaggerated muscle deoxygenation during the ramp test (248% vs 49%). Conversely, markers of metabolic stress and recovery from the exhaustive ramp test improved more after the ECC than the CON protocol, that is, peak blood lactate (−9% vs +20%) and peak SmO2 (+7% vs −7%). Anaerobic muscle power only improved after the CON protocol (+18% vs −15%). Conclusions: This study indicates the potential of the implemented CON and ECC protocols of pedaling-type interval exercise to improve oxygen metabolism of exercised muscle groups while maintaining or even increasing the Ppeak. The ECC training protocol seemingly provided a lower cardiovascular stimulus in patients with CAD while specifically enhancing the reoxygenation and blood lactate clearance in recruited muscle groups during recovery from exercise. Trial Registration: ClinicalTrials.gov NCT02845063; https://clinicaltrials.gov/ct2/show/NCT02845063

A healthy lifestyle reduces the risk of cardio-vascular disease. As wheelchair-bound individuals with spinal cord injury (SCI) are challenged in their activities, promoting and coaching an active lifestyle is especially relevant. Although there are many commercial activity trackers available for the able-bodied population, including those providing feedback about energy expenditure (EE), activity trackers for the SCI population are largely lacking, or are limited to a small set of activities performed in controlled settings. The aims of the present study were to develop and validate an algorithm based on inertial measurement unit (IMU) data to continuously monitor EE in wheelchair-bound individuals with a SCI, and to establish reference activity values for a healthy lifestyle in this population. For this purpose, EE was measured in 30 subjects each wearing four IMUs during 12 different physical activities, randomly selected from a list of 24 activities of daily living. The proposed algorithm consists of three parts: resting EE estimation based on multi-linear regression, an activity classification using a k-nearest-neighbors algorithm, and EE estimation based on artificial neural networks (ANNs). The mean absolute estimation error for the ANN-based algorithm was 14.4% compared to indirect calorimeter measurements. Based on reference values from the literature and the data collected within this study, we recommend wheeling 3 km per day for a healthy lifestyle in wheelchair-bound SCI individuals. Combining the proposed algorithm with a recommendation for physical activity provides a powerful tool for the promotion of an active lifestyle in the SCI population, thereby reducing the risk for secondary diseases.

Psychophysical procedures are applied in various fields to assess sensory thresholds. During experiments, sampled psychometric functions are usually assumed to be stationary. However, perception can...

BACKGROUND Cardiovascular diseases are the leading causes of death worldwide, and coronary artery disease (CAD) is one of the most common causes of death in Europe. Leading cardiac societies recommend exercise as an integral part of cardiovascular rehabilitation because it reduces the morbidity and mortality of patients with CAD. Continuous low-intensity exercise using shortening muscle actions (concentric, CON) is a common training modality during cardiovascular rehabilitation. However, a growing clinical interest has been recently developed in high-intensity interval training (HIIT) for stable patients with CAD. Exercise performed with lengthening muscle actions (eccentric, ECC) could be tolerated better by patients with CAD as they can be performed with higher loads and lower metabolic cost than CON exercise. OBJECTIVE We developed a clinical protocol on a soft robot to compare cardiovascular and muscle effects of repeated and work-matched CON versus ECC pedaling-type interval exercise between patients with CAD during cardiovascular rehabilitation. This study aims to ascertain whether the developed training protocols affect peak oxygen uptake (VO2peak), peak aerobic power output (Ppeak), and parameters of muscle oxygen saturation (SmO2) during exercise, and anaerobic muscle power. METHODS We will randomize 20-30 subjects to either the CON or ECC group. Both groups will perform a ramp test to exhaustion before and after the training period to measure cardiovascular parameters and SmO2. Moreover, the aerobic skeletal muscle power (Ppeak) is measured weekly during the 8-week training period using a simulated squat jump and a counter movement jump on the soft robot and used to adjust the training load. The pedaling-type interval exercise on the soft robot is performed involving either CON or ECC muscle actions. The soft robotic device being used is a closed kinetic chain, force-controlled interactive training, and testing device for the lower extremities, which consists of two independent pedals and free footplates that are operated by pneumatic artificial muscles. RESULTS The first patients with CAD, who completed the training, showed protocol-specific improvements, reflecting, in part, the lower aerobic training status of the patient completing the CON protocol. Rehabilitation under the CON protocol, more than under the ECC protocol, improved cardiovascular parameters, that is, VO2peak (+26% vs −6%), and Ppeak (+20% vs 0%), and exaggerated muscle deoxygenation during the ramp test (248% vs 49%). Conversely, markers of metabolic stress and recovery from the exhaustive ramp test improved more after the ECC than the CON protocol, that is, peak blood lactate (−9% vs +20%) and peak SmO2 (+7% vs −7%). Anaerobic muscle power only improved after the CON protocol (+18% vs −15%). CONCLUSIONS This study indicates the potential of the implemented CON and ECC protocols of pedaling-type interval exercise to improve oxygen metabolism of exercised muscle groups while maintaining or even increasing the Ppeak. The ECC training protocol seemingly provided a lower cardiovascular stimulus in patients with CAD while specifically enhancing the reoxygenation and blood lactate clearance in recruited muscle groups during recovery from exercise. CLINICALTRIAL ClinicalTrials.gov NCT02845063; https://clinicaltrials.gov/ct2/show/NCT02845063

Psychophysical procedures are applied in various fields to assess sensory thresholds. During experiments, sampled psychometric functions are usually assumed to be stationary. However, perception can be altered, for example by loss of attention to the presentation of stimuli, leading to biased data which results in poor threshold estimates. The few existing approaches attempting to identify non-stationarities either detect only whether there was a change in perception, or are not suitable for experiments with a relatively small number of trials (e.g., < 300). We present a method to detect inattention periods on a trial-by-trial basis to improve threshold estimates in psychophysical experiments using the adaptive sampling procedure Parameter Estimation by Sequential Testing (PEST). The performance of the algorithm was evaluated in computer simulations modeling inattention, and tested in a behavioral experiment on proprioceptive difference threshold assessment in 20 stroke patients, a population where attention deficits are likely to be present. Simulations showed that estimation errors could be reduced by up to 77% for inattentive subjects, even in sequences with less than 100 trials. In the behavioral data, inattention was detected in 14% of assessments, and applying the proposed algorithm resulted in reduced test-retest variability in 73% of these corrected assessments pairs. The algorithm complements existing approaches and can be adapted to sampling procedures other than PEST. Besides being applicable post-hoc , it could also be used online to prevent collection of biased data. This could have important implications in assessment practice by shortening experiments and improving estimates.