Improved Jacobian matrix estimation applied to snake robots.

Two manipulator Jacobian matrix estimators for constrained planar snake robots are developed and tested, which enables the implementation of Jacobian-based obstacle-aided locomotion (OAL) control schemes. These schemes use obstacles in the robot's vicinity to obtain propulsion. The devised estimators infer manipulator Jacobians for constrained planar snake robots in situations where the positions and number of surrounding obstacle constraints might change or are not precisely known. The first proposed estimator is an adaptation of contemporary research in soft robots and builds on convex optimization. The second estimator builds on the unscented Kalman filter. By simulations, we evaluate and compare the two devised algorithms in terms of their statistical performance, execution times, and robustness to measurement noise. We find that both algorithms lead to Jacobian matrix estimates that are similarly useful to predict end-effector movements. However, the unscented filter approach requires significantly lower computing resources and is not poised by convergence issues displayed by the convex optimization-based method. We foresee that the estimators may have use in other fields of research, such as soft robotics and visual servoing. The estimators may also be adapted for use in general non-planar snake robots.

Modeling Movement-Induced Errors in AC Electromagnetic Trackers.

Error analysis of electromagnetic motion tracking systems is of growing interest to many researchers. Under sensor movement, it is logical to presume that the error in position and orientation measurements will increase due to the linearization used in the algorithms, among other reasons. In this article, we analyze theoretically the error, that results from linearization, in position measurement of the Polhemus tracking system for a moving sensor. We derive formulas to estimate this error in terms of the sensor position and speed. Then, we verify these formulas by numerical simulations.

Low-Order Nonlinear Animal Model of Glucose Dynamics for a Bihormonal Intraperitoneal Artificial Pancreas.

OBJECTIVE: The design of an Artificial Pancreas (AP) to regulate blood glucose levels requires reliable control methods. Model Predictive Control has emerged as a promising approach for glycemia control. However, model-based control methods require computationally simple and identifiable mathematical models that represent glucose dynamics accurately, which is challenging due to the complexity of glucose homeostasis. METHODS: In this work, a simple model is deduced to estimate blood glucose concentration in subjects with Type 1 Diabetes Mellitus (T1DM). Novel features in the model are power-law kinetics for intraperitoneal insulin absorption and a separate glucagon sensitivity state. Profile likelihood and a method based on singular value decomposition of the sensitivity matrix are carried out to assess parameter identifiability and guide a model reduction for improving the identification of parameters. RESULTS: A reduced model with 10 parameters is obtained and calibrated, showing good fit to experimental data from pigs where insulin and glucagon boluses were delivered in the intraperitoneal cavity. CONCLUSION: A simple model with power-law kinetics can accurately represent glucose dynamics submitted to intraperitoneal insulin and glucagon injections. The reduced model was found to exhibit local practical as well as structural identifiability. IMPORTANCE: The proposed model facilitates intraperitoneal bi-hormonal model-based closed-loop control in animal trials.

Modelling and simulation of occlusions in insulin pumps.

An open source simulation model of the mechanical properties of a fully functional insulin pump was made in Matlab Simscape. The model simulates realistic behavior of an insulin pump, parts of which are validated against real-world systems. Simulations include mechanical forces and internal pressures, and the following fluid dynamics. Failure modes, such as occlusions, can be simulated and the resulting simulations can give new insights on how these failures affect the pump and how to detect them.Clinical relevance- Realistic pump simulations can be used to analyze how pump failures affect the system and in turn how to most effectively detect them before posing a hazard to the user, increasing the safety and reliability of the system.

Rigid head-neck responses to unpredictable perturbations in patients with long standing neck pain does not change with treatment.

In a previous study we have shown that patients with long standing non-specific neck-pain display more rigid neck movement behavior than controls in response to unpredictable perturbations. In the present study we investigated head/neck motor control in patients with neck-pain during a course of physiotherapy intervention and the associations with pain, neck disability and kinesiophobia. In this longitudinal observational study, 72 patients with non-specific neck-pain were exposed to unpredictable horizontal rotations by means of an actuated chair in three conditions; with a visual reference, and without vision with and without a cognitive task before first consultation with physiotherapist, after 2 weeks and 2 months of intervention. The neck movements were analyzed in the frequency domain to cover voluntarily and reflex controlled responses. Questionnaires encompassed Neck Disability Index, Tampa Scale of Kinesiophobia, and the Numerical Rating Scale for current pain. The results showed that the response pattern for the amplitudes of movement between head and trunk across frequencies did not change over time, whereas some changes in timing were found for some frequencies. Pain, neck disability, and kinesiophobia improved after intervention, but were not significantly associated with neck movement responses to perturbations across time or condition. Although physiotherapy intervention improved self-reported function, the rigid responses to unpredictable perturbations remained unchanged. This indicates altered function in reflex mediated control mechanisms, i.e., the vestibulocollic and the cervicocollic reflex systems that control the head in space and on the trunk. Future research should further investigate pain related changes in reflex systems and whether alterations in these systems are modifiable.

Pattern Recognition Reveals Characteristic Postprandial Glucose Changes: Non-Individualized Meal Detection in Diabetes Mellitus Type 1.

Accurate continuous glucose monitoring (CGM) is essential for fully automated glucose control in diabetes mellitus type 1. State-of-the-art glucose control systems automatically regulate the basal insulin infusion. Users still need to manually announce meals to dose the prandial insulin boluses. An automated meal detection could release the user and improve the glucose regulation. In this study, patterns in the postprandial CGM data are exploited for meal detection. Binary classifiers are trained to recognize the postprandial pattern in horizons of the estimated glucose rate of appearance and in CGM data. The appearance rate is determined by moving horizon estimation based on a simple model. Linear discriminant analysis (LDA) is used for classification. The proposed method is compared to methods that detect meals when thresholds are violated. Diabetes care data from 12 free-living pediatric patients was downloaded during regular screening. Experts identified meals and their start by retrospective evaluation. The classification was tested by cross-validation. Compared to the threshold-based methods, LDA showed higher sensitivity to meals with a low rate of false alarms. Classifying horizons outperformed the other methods also with respect to time of detection. The onset of meals can be detected by pattern recognition based on estimated model states and consecutive CGM measurements. No individual tuning is necessary. This makes the method easily adopted in the clinical practice.

Why intraperitoneal glucose sensing is sometimes surprisingly rapid and sometimes slow: A hypothesis.

The artificial pancreas requires fast and reliable glucose measurements. The peritoneal space has shown promising results, and in one of our studies we detected glucose changes in the peritoneal space already at the same time as in the femoral artery. The peritoneal lining is highly vascularised, covered by a single layer of mesothelial cells and therefore easily accessible for proper sensor technology, e.g. optical technology. We hypothesize that the rapid intraperitoneal glucose dynamics observed in our study was possible because the sensors were located directly at the peritoneal lining, at the point where the glucose molecules entered the peritoneal space. Glucose travels slowly in fluids by diffusion, and a longer distance between the sensor and the peritoneal lining would consequently result in slower dynamics. We therefore propose to place the glucose sensor in an artificial pancreas as closely to the peritoneal lining as possible, or even utilize appropriate sensor technology to measure glucose in the peritoneal lining itself.

Frequency-dependent deficits in head steadiness in patients with nonspecific neck pain.

Motor control impairments are reported in patients with nonspecific neck pain but the particular deficits in underlying regulatory systems are not known. Head steadiness is controlled both by voluntary and reflex systems that are predominantly effective within different frequency intervals. The aim of the present study was to investigate within which frequency range(s) potential motor control deficits may reside. The ability to keep the head stationary in space in response to unpredictable perturbations was tested in 71 patients with nonspecific neck pain and 17 healthy controls. Participants were exposed to pseudorandom horizontal rotations across 10 superimposed frequencies (0.185-4.115 Hz) by means of an actuated chair in three conditions; with a visual reference, and without vision with, and without a cognitive task. Below 1 Hz, patients kept the head less stable in space compared to healthy controls. Between 1 and 2 Hz, the head was stabilized on the trunk in both groups. Patients kept the head more stable relative to the trunk than relative to space compared to healthy controls. This was interpreted as higher general neck muscle co-activation in patients, which may be explained by altered voluntary control, or/and upregulated gamma motor neuron activity which increases the contribution of reflex-mediated muscle activation. Alternatively, increased muscle activity is secondary to vestibular deficits.

Data driven filtering of bowel sounds using multivariate empirical mode decomposition.

BACKGROUND: The analysis of abdominal sounds can help to diagnose gastro-intestinal diseases. Sounds originating from the stomach and the intestine, the so-called bowel sounds, occur in various forms. They are described as loose successions or clusters of rather sudden bursts. Realistic recordings of abdominal sounds are contaminated with noise and artifacts from which the bowel sounds must be differentiated. METHODS: The proposed intrinsic mode function-fractal dimension (IMF-FD) filtering utilizes the property of the multivariate empirical mode decomposition (MEMD) to behave as a series of band pass filters. The MEMD decomposes the abdominal signal into its different frequency components. The resulting intrinsic mode functions (IMFs) are modulated in amplitude and frequency where transient sonic events occur. Based on the complexity of the IMFs, measured by their fractal dimension (FD) in sliding windows, the information-carrying IMFs are selected. The filtered signal is formed as the superposition of all selected IMFs. The IMF-FD filter not only enhances the non-linear components of the original signal but also segments them from the rest. Another important aspect of this work is that typical artifacts that occur in the same frequency range as bowel sounds can be subsequently eliminated by heuristic rules. CONCLUSIONS: The method is tested on a realistic, contaminated data set with promising performance: close to 100% of the manually labeled bowel sounds are identified.

Feasibility of Early Meal Detection Based on Abdominal Sound.

In classical approaches for an artificial pancreas, continuous glucose monitoring (CGM) is the only measured variable used for insulin dosing and additional control functions. The CGM values are subject to time delays and slow dynamics between blood and the sensing location. These time lags compromise the controller's performance in maintaining (near to) normal glucose levels. Meal information could enhance the control outcome. However, meal announcement by the user is not reliable, and it takes 30 min to 40 min from meal onset until a meal is detected by methods based on CGM. In this pilot study, the use of bowel sounds for meal detection was investigated. In particular, we focused on whether bowel sounds change qualitatively during or shortly after meal ingestion. After fasting for at least 4 h, 11 healthy volunteers ingested a lunch meal at their usual time. Abdominal sound was recorded by a condenser microphone that was attached to the right upper quadrant of the abdomen by medical tape. Features that describe the power distribution over the frequency spectrum were extracted and used for classification by support vector machines. These classifiers were trained in a leave-one-out cross-validation scheme. Meals could be detected on average 10 min (std: 4.4 min) after they had started. Half of these were detected without false alarms. This shows that abdominal sound monitoring could provide an early meal detection. Further studies should investigate this possibility on a larger population in more general settings.

Kalman Smoothing for Objective and Automatic Preprocessing of Glucose Data.

A method for preprocessing a time series of glucose measurements based on Kalman smoothing is presented. Given a glucose data time series that may be irregularly sampled, the method outputs an interpolated time series of glucose estimates with mean and variance. The method can provide homogenization of glucose data collected from different devices by using separate measurement noise parameters for differing glucose measurement equipment. We establish a link between the ISO 15197 standard and the measurement noise variance used by the Kalman smoother for self-monitoring of blood glucose (SMBG) measurements. The method provides phaseless smoothing, and it can automatically correct errors in the original datasets like small fallouts and erroneous readings when surrounding data allow. The estimated variance can be used for deciding at which times the data are trustworthy. The method can be used as a preprocessing step in many kinds of glucose data processing and analysis tasks, such as computing the mean absolute relative deviation between measurement systems or estimating the plasma-to-interstitial fluid glucose dynamics of continuous glucose monitor or flash glucose monitor (FGM) signals. The method is demonstrated on SMBG and FGM glucose data from a clinical study. A MATLAB implementation of the method is publicly available.

Effect of sensor location on continuous intraperitoneal glucose sensing in an animal model.

BACKGROUND: In diabetes research, the development of the artificial pancreas has been a major topic since continuous glucose monitoring became available in the early 2000's. A prerequisite for an artificial pancreas is fast and reliable glucose sensing. However, subcutaneous continuous glucose monitoring carries the disadvantage of slow dynamics. As an alternative, we explored continuous glucose sensing in the peritoneal space, and investigated potential spatial differences in glucose dynamics within the peritoneal cavity. As a secondary outcome, we compared the glucose dynamics in the peritoneal space to the subcutaneous tissue. MATERIAL AND METHODS: Eight-hour experiments were conducted on 12 anesthetised non-diabetic pigs. Four commercially available amperometric glucose sensors (FreeStyle Libre, Abbott Diabetes Care Ltd., Witney, UK) were inserted in four different locations of the peritoneal cavity and two sensors were inserted in the subcutaneous tissue. Meals were simulated by intravenous infusions of glucose, and frequent arterial blood and intraperitoneal fluid samples were collected for glucose reference. RESULTS: No significant differences were discovered in glucose dynamics between the four quadrants of the peritoneal cavity. The intraperitoneal sensors responded faster to the glucose excursions than the subcutaneous sensors, and the time delay was significantly smaller for the intraperitoneal sensors, but we did not find significant results when comparing the other dynamic parameters.

Differences Between Flash Glucose Monitor and Fingerprick Measurements.

Freestyle Libre (FL) is a factory calibrated Flash Glucose Monitor (FGM). We investigated Mean Absolute Relative Difference (MARD) between Self Monitoring of Blood Glucose (SMBG) and FL measurements in the first day of sensor wear in 39 subjects with Type 1 diabetes. The overall MARD was 12.3%, while the individual MARDs ranged from 4% to 25%. Five participants had a MARD ≥ 20%. We estimated bias and lag between the FL and SMBG measurements. The estimated biases range from -1.8 mmol / L to 1.4 mmol / L , and lags range from 2 min to 24 min . Bias is identified as a main cause of poor individual MARDs. The biases seem to persist in days 2⁻7 of sensor usage. All cases of MARD ≥ 20% in the first day are eliminated by bias correction, and overall MARD is reduced from 12.3% to 9.2%, indicating that adding support for voluntary user-supplied bias correction in the FL could improve its performance.

A Review of the Current Challenges Associated with the Development of an Artificial Pancreas by a Double Subcutaneous Approach.

INTRODUCTION: Patients with diabetes type 1 (DM1) struggle daily to achieve good glucose control. The last decade has seen a rush of research groups working towards an artificial pancreas (AP) through the application of a double subcutaneous approach, i.e., subcutaneous (SC) continuous glucose monitoring (CGM) and continuous subcutaneous insulin infusion. Few have focused on the fundamental limitations of this approach, especially regarding outcome measures beyond time in range. METHODS: Based on insulin physiology, the limitations of CGM, SC insulin absorption, meal challenge, and physical activity in DM1 patients, we discuss the limitations of the double SC approach. Finally, we discuss safety measures and the achievements reported in some recent AP studies that have utilized the double SC approach. RESULTS: Most studies show that a double SC AP increases the time in range compared to a sensor-augmented insulin pump and shortens the time in hypoglycemia. Despite these achievements, the proportion of time spent in hyperglycemia is still roughly 20-40%, and hypoglycemia is still present 1-4% of the time. The main factors limiting further progress are the latency of SC CGM (at least 5-10 min) and the slow pharmacokinetics of SC-delivered fast-acting insulin. The maximum blood insulin level is reached after 45 min and the maximum glucose-lowering effect is observed after 1.5-2 h, while the glucose-lowering effect lasts for at least 5 h. CONCLUSIONS: Although using a double SC AP leads to significant improvements in glucose control, the SC approach has severe limitations that hamper further progress towards a robust AP.

Mechanisms controlling human head stabilization during random rotational perturbations in the horizontal plane revisited.

This study repeats the experimental protocol for investigation of head stabilization in healthy humans, described by Keshner and Peterson (1995) but with a modification of the analysis. Head movements were considered with respect to the room instead of relative to the trunk. The aim was to investigate the approximate contribution of reflex and voluntary control across perturbing frequencies and conditions with modulation of visual information and mental attention and discuss the resulting outcome while comparing methods. Seventeen healthy individuals were asked to keep the head steady in space while subjected to pseudorandom rotational perturbations in the horizontal plane, firmly seated on an actuated chair. Both methods confirmed the results for gain in previous studies showing fair ability to keep the head steady in space below 1 Hz with vision. Compensation deteriorated when vision was removed and worsened further with addition of a mental task. Between 1 and 2 Hz, unity gain occurred between head and trunk movements, whereas above 2 Hz the head moved more than the trunk. For phase angles, the original method demonstrated a phase split occurring from ~1 Hz, a purely mathematical artifact that caused subjects with virtually identical movements to appear as significantly different. This artifact was eliminated by analyzing the head-room relative to trunk-room rather than head-trunk relative to trunk-room angles, thus preventing potentially erroneous interpretations of the results.

Frequency Analysis and Feature Reduction Method for Prediction of Cerebral Palsy in Young Infants.

The aim of this paper is to achieve a model for prediction of cerebral palsy based on motion data of young infants. The prediction is formulated as a classification problem to assign each of the infants to one of the healthy or with cerebral palsy groups. Unlike formerly proposed features that are mostly defined in the time domain, this study proposes a set of features derived from frequency analysis of infants' motions. Since cerebral palsy affects the variability of the motions, and frequency analysis is an intuitive way of studying variability, suggested features are suitable and consistent with the nature of the condition. In the current application, a well-known problem, few subjects and many features, was initially encountered. In such a case, most classifiers get trapped in a suboptimal model and, consequently, fail to provide sufficient prediction accuracy. To solve this problem, a feature selection method that determines features with significant predictive ability is proposed. The feature selection method decreases the risk of false discovery and, therefore, the prediction model is more likely to be valid and generalizable for future use. A detailed study is performed on the proposed features and the feature selection method: the classification results confirm their applicability. Achieved sensitivity of 86%, specificity of 92% and accuracy of 91% are comparable with state-of-the-art clinical and expert-based methods for predicting cerebral palsy.

Evidence for a general stiffening motor control pattern in neck pain: a cross sectional study.

BACKGROUND: Neck pain is associated with several alterations in neck motion and motor control. Previous studies have investigated single constructs of neck motor control, while few have applied a comprehensive set of tests to investigate cervical motor control. This comparative cross- sectional study aimed to investigate different motor control constructs in neck pain patients and healthy controls. METHODS: A total of 166 subjects participated in the study, 91 healthy controls (HC) and 75 neck pain patients (NP) with long-lasting moderate to severe neck pain. Neck flexibility, proprioception, head steadiness, trajectory movement control, and postural sway were assessed using a 3D motion tracking system (Liberty). The different constructs of neck motion and motor control were based on tests used in previous studies. RESULTS: Neck flexibility was lower in NP compared to HC, indicated by reduced cervical ROM and conjunct motion. Movement velocity was slower in NP compared to HC. Tests of head steadiness showed a stiffer movement pattern in NP compared to HC, indicated by lower head angular velocity. NP patients departed less from a predictable trajectory movement pattern (figure of eight) compared to healthy controls, but there was no difference for unpredictable movement patterns (the Fly test). No differences were found for postural sway in standing with eyes open and eyes closed. However, NP patients had significantly larger postural sway when standing on a balance pad. Proprioception did not differ between the groups. Largest effect sizes (ES) were found for neck flexibility (ES range: 0.2-0.8) and head steadiness (ES range: 1.3-2.0). Neck flexibility was the only construct that showed a significant association with current neck pain, while peak velocity was the only variable that showed a significant association with kinesiophobia. CONCLUSIONS: NP patients showed an overall stiffer and more rigid neck motor control pattern compared to HC, indicated by lower neck flexibility, slower movement velocity, increased head steadiness and more rigid trajectory head motion patterns. Only neck flexibility showed a significant association with clinical features in NP patients.

Frequency-based features for early cerebral palsy prediction.

In this paper we aim at predicting cerebral palsy, the most serious and lifelong motor function disorder in children, at an early age by analysing infants' motion data. An essential step for doing so is to extract informative features with high class separability. We propose a set of features derived from frequency analysis of the motion data. Then, we evaluate the practicality of our features on one of the richest data sets collected to study this disease. In this data set, the motion data are extracted from both electromagnetic sensors as well as video camera. The proposed features are used for classifying both data sets. Using these features, we manage to achieve promising classification performance. Classification accuracy of 91% for the sensor data and 88% for the video-derived data show not only the advantage of employing these features for predicting cerebral palsy, but also that replacing electromagnetic sensors with a video camera is feasible.

System training and assessment in simultaneous proportional myoelectric prosthesis control.

BACKGROUND: Pattern recognition control of prosthetic hands take inputs from one or more myoelectric sensors and controls one or more degrees of freedom. However, most systems created allow only sequential control of one motion class at a time. Additionally, only recently have researchers demonstrated proportional myoelectric control in such systems, an option that is believed to make fine control easier for the user. Recent developments suggest improved reliability if the user follows a so-called prosthesis guided training (PGT) scheme. METHODS: In this study, a system for simultaneous proportional myoelectric control has been developed for a hand prosthesis with two motor functions (hand open/close, and wrist pro-/supination). The prosthesis has been used with a prosthesis socket equivalent designed for normally-limbed subjects. An extended version of PGT was developed for use with proportional control. The control system's performance was tested for two subjects in the Clothespin Relocation Task and the Southampton Hand Assessment Procedure (SHAP). Simultaneous proportional control was compared with three other control strategies implemented on the same prosthesis: mutex proportional control (the same system but with simultaneous control disabled), mutex on-off control, and a more traditional, sequential proportional control system with co-contractions for state switching. RESULTS: The practical tests indicate that the simultaneous proportional control strategy and the two mutex-based pattern recognition strategies performed equally well, and superiorly to the more traditional sequential strategy according to the chosen outcome measures. CONCLUSIONS: This is the first simultaneous proportional myoelectric control system demonstrated on a prosthesis affixed to the forearm of a subject. The study illustrates that PGT is a promising system training method for proportional control. Due to the limited number of subjects in this study, no definite conclusions can be drawn.