Identification of Movements and Postures Using Wearable Sensors for Implementation in a Bi-Hormonal Artificial Pancreas System.

BACKGROUND: Closed loop bi-hormonal artificial pancreas systems, such as the artificial pancreas (AP™) developed by Inreda Diabetic B.V., control blood glucose levels of type 1 diabetes mellitus patients via closed loop regulation. As the AP™ currently does not classify postures and movements to estimate metabolic energy consumption to correct hormone administration levels, considerable improvements to the system can be made. Therefore, this research aimed to investigate the possibility to use the current system to identify several postures and movements. METHODS: seven healthy participants took part in an experiment where sequences of postures and movements were performed to train and assess a computationally sparing algorithm. RESULTS: Using accelerometers, one on the hip and two on the abdomen, user-specific models achieved classification accuracies of 86.5% using only the hip sensor and 87.3% when including the abdomen sensors. With additional accelerometers on the sternum and upper leg for identification, 90.0% of the classified postures and movements were correct. CONCLUSIONS: The current hardware configuration of the AP™ poses no limitation to the identification of postures and movements. If future research shows that identification can still be done accurately in a daily life setting, this algorithm may be an improvement for the AP™ to sense physical activity.

Pilot study on VF-waveform based algorithms for early detection of acute myocardial infarction during out-of-hospital cardiac arrest.

INTRODUCTION: On-scene detection of acute coronary occlusion (ACO) during ongoing ventricular fibrillation (VF) may facilitate patient-tailored triage and treatment during cardiac arrest. Experimental studies have demonstrated the diagnostic potential of the amplitude spectrum area (AMSA) of the VF-waveform to detect myocardial infarction (MI). In follow-up, we performed this clinical pilot study on VF-waveform based discriminative models to diagnose acute MI due to ACO in real-world VF-patients. METHODS: In our registry of VF-patients transported to a tertiary hospital (Nijmegen, The Netherlands), we studied patients with high-quality VF-registrations. We calculated VF-characteristics prior to the first shock, and first-to-second shock changes (Δ-characteristics). Primary aim was to assess the discriminative ability of the AMSA to detect patients with ACO. Secondarily, we investigated the discriminative value of adding ΔAMSA-measures using machine learning algorithms. Model performances were assessed using C-statistics. RESULTS: In total, there were 67 VF-patients with and 34 without an ACO, and baseline characteristics did not differ significantly. Based on the AMSA prior to the first defibrillation attempt, discrimination between ACO and non-ACO was possible, with a C-statistic of 0.66 (0.56-0.75). The discriminative model using AMSA + ΔAMSA yielded a C-statistic of 0.80 (0.69-0.88). CONCLUSION: These clinical pilot data confirm previous experimental findings that early detection of MI using VF-waveform analysis seems feasible, and add insights on the diagnostic impact of accounting for first-to-second shock changes in VF-characteristics. Confirmative studies in larger cohorts and with a variety of VF-algorithms are warranted to further investigate the potential of this innovative approach.

Evaluation of a Dedicated Radiofrequency Carotid PET/MRI Coil.

Carotid radiofrequency coils inside a PET/MRI system can result in PET quantification errors. We compared the performance of a dedicated PET/MRI carotid coil against a coil for MRI-only use. An 18F-fluorodeoxyglucose (18F-FDG) phantom was scanned without and with an MRI-only coil and with the PET/MRI coil. The decay-corrected normalized activity was compared for the different coil configurations. Eighteen patients were scanned with the three coil configurations. The maximal standardized uptake values (SUVmax) and signal-to-noise ratios (SNR) were calculated. Repeated measures ANOVA was performed to assess the differences in SUVmax and SNR between the coil configurations. In the phantom study, the PET/MRI coil demonstrated a slight decrease (<5%), while the MRI-only coil showed a substantial decrease (up to 10%) in normalized activity at the position of coil elements compared to no dedicated coil configuration. In the patient study, the SUVmax values for both no surface coil (3.59 ± 0.15) and PET/MRI coil (3.54 ± 0.15) were significantly higher (p = 0.03 and p = 0.04, respectively) as compared to the MRI-only coil (3.28 ± 0.16). No significant difference was observed between PET/MRI and no surface coil (p = 1.0). The SNR values for both PET/MRI (7.31 ± 0.44) and MRI-only (7.62 ± 0.42) configurations demonstrated significantly higher (p < 0.001) SNR values as compared to the no surface coil (3.78 ± 0.22), while no significant difference was observed in SNR between the PET/MRI and MRI-only coil (p = 1.0). This study demonstrated that the PET/MRI coil can be used for PET imaging without requiring attenuation correction while acquiring high-resolution MR images.

An empirical model for educational simulation of cervical dilation in first-stage labor.

BACKGROUND: Several models for educational simulation of labor and delivery were published in the literature and incorporated into a commercially available training simulator (CAE Healthcare Lucina). However, the engine of this simulator does not include a model for the clinically relevant indicators: uterine contraction amplitude and frequency, and cervical dilation. In this paper, such a model is presented for the primigravida in normal labor. METHODS: The conceptual and mathematical models represent oxytocin release by the hypothalamus, oxytocin pharmacokinetics, and oxytocin effect on uterine contractions, cervical dilation, and (positive) feedback from cervical dilation to oxytocin release by the hypothalamus. RESULTS: Simulation results for cervical dilation are presented, together with target data for a normal primigravida. Corresponding oxytocin concentrations and amplitude and frequency of uterine contractions are also presented. CONCLUSION: An original empirical model for educational simulation of oxytocin concentration, uterine contractions, and cervical dilation in first-stage labor is presented. Simulation results for cervical dilation match target data for a normal patient. The model forms a basis for taking into account more independent variables and patient profiles and can thereby considerably expand the range of training scenarios that can be simulated.