New ex vivo method to objectively assess insulin spatial subcutaneous dispersion through time during pump basal-rate based administration.

Glycemic variability remains frequent in patients with type 1 diabetes treated with insulin pumps. Heterogeneous spreads of insulin infused by pump in the subcutaneous (SC) tissue are suspected but were barely studied. We propose a new real-time ex-vivo method built by combining high-precision imaging with simultaneous pressure measurements, to obtain a real-time follow-up of insulin subcutaneous propagation. Human skin explants from post-bariatric surgery are imaged in a micro-computed tomography scanner, with optimised parameters to reach one 3D image every 5 min during 3 h of 1UI/h infusion. Pressure inside the tubing is recorded. A new index of dispersion (IoD) is introduced and computed upon the segmented 3D insulin depot per time-step. Infusions were hypodermal in 58.3% among 24 assays, others being intradermal or extradermal. Several minor bubbles and one occlusion were observed. IoD increases with time for all injections. Inter-assay variability is the smallest for hypodermal infusions. Pressure elevations were observed, synchronised with air bubbles arrivals in the tissue. Results encourage the use of this method to compare infusion parameters such as pump model, basal rate, catheter characteristics, infusion site characteristics or patient phenotype.

Symptoms assessment and decision to treat patients with advanced Parkinson's disease based on wearables data.

Body-worn sensors (BWS) could provide valuable information in the management of Parkinson's disease and support therapeutic decisions based on objective monitoring. To study this pivotal step and better understand how relevant information is extracted from BWS results and translated into treatment adaptation, eight neurologists examined eight virtual cases composed of basic patient profiles and their BWS monitoring results. Sixty-four interpretations of monitoring results and the subsequent therapeutic decisions were collected. Relationship between interrater agreements in the BWS reading and the severity of symptoms were analyzed via correlation studies. Logistic regression was used to identify associations between the BWS parameters and suggested treatment modifications. Interrater agreements were high and significantly associated with the BWS scores. Summarized BWS scores reflecting bradykinesia, dyskinesia, and tremor predicted the direction of treatment modifications. Our results suggest that monitoring information is robustly linked to treatment adaptation and pave the way to loop systems able to automatically propose treatment modifications from BWS recordings information.

Body-Worn Sensors for Parkinson's disease: A qualitative approach with patients and healthcare professionals.

Body-Worn Sensors (BWS) provide reliable objective and continuous assessment of Parkinson's disease (PD) motor symptoms, but their implementation in clinical routine has not yet become widespread. Users' perceptions of BWS have not been explored. This study intended to evaluate the usability, user experience (UX), patients' perceptions of BWS, and health professionals' (HP) opinions on BWS monitoring. A qualitative analysis was performed from semi-structured interviews conducted with 22 patients and 9 HP experts in PD. Patients completed two interviews before and after the BWS one-week experiment, and they answered two questionnaires assessing the usability and UX. Patients rated the three BWS usability with high scores (SUS median [range]: 87.5 [72.5-100]). The UX across all dimensions of their interaction with the BWS was positive. During interviews, all patients and HP expressed interest in BWS monitoring. Patients' hopes and expectations increased the more they learned about BWS. They manifested enthusiasm to wear BWS, which they imagined could improve their PD symptoms. HP highlighted needs for logistical support in the implementation of BWS in their practice. Both patients and HP suggested possible uses of BWS monitoring in clinical practice, for treatment adjustments for example, or for research purposes. Patients and HP shared ideas about the use of BWS monitoring, although patients may be more likely to integrate BWS into their disease follow-up compared to HP in their practice. This study highlights gaps that need to be fulfilled to facilitate BWS adoption and promote their potential.

New physiological bench test reproducing nocturnal breathing pattern of patients with sleep disordered breathing.

Previous studies have shown that Automatic Positive Airway Pressure devices display different behaviors when connected to a bench using theoretical respiratory cycle scripts. However, these scripts are limited and do not simulate physiological behavior during the night. Our aim was to develop a physiological bench that is able to simulate patient breathing airflow by integrating polygraph data. We developed an algorithm analyzing polygraph data and transformed this information into digital inputs required by the bench hardware to reproduce a patient breathing profile on bench. The inputs are respectively the simulated respiratory muscular effort pressure input for an artificial lung and the sealed chamber pressure to regulate the Starling resistor. We did simulations on our bench for a total of 8 hours and 59 minutes for a breathing profile from the demonstration recording of a Nox T3 Sleep Monitor. The simulation performance results showed that in terms of relative peak-valley amplitude of each breathing cycle, simulated bench airflow was biased by only 1.48% ± 6.80% compared to estimated polygraph nasal airflow for a total of 6,479 breathing cycles. For total respiratory cycle time, the average bias ± one standard deviation was 0.000 ± 0.288 seconds. For patient apnea events, our bench simulation had a sensitivity of 84.7% and a positive predictive value equal to 90.3%, considering 149 apneas detected both in polygraph nasal simulated bench airflows. Our new physiological bench would allow personalizing APAP device selection to each patient by taking into account individual characteristics of a sleep breathing profile.

Gait Monitoring and Walk Distance Estimation With an Accelerometer During 6-Minute Walk Test.

BACKGROUND: The 6-min walk test (6MWT) encompasses potential and untapped information related to exercise capacity. However, this test does not yield any information about gait pattern. Recently, we used a ventilatory polygraph to reveal respiratory adaptation during the 6MWT with subjects having high or low body mass index (BMI). In this study, we aimed to determine gait parameters with the same device, which integrates an accelerometer. METHODS: Using a 30-m corridor, steps and U-turns were detected with a custom-made algorithm, compared to video recordings as a reference method, and analyzed offline. From the vertical acceleration signal, we were able to determine cadence and step length, and we could calculate the total distance covered in 6 min (6MWD). We then compared these variables between subjects with low BMI (n = 13 subjects) or high BMI (n = 29 subjects). RESULTS: Steps and U-turn detection correlated with video results (r = 0.99, P < .001 for both). The 6MWD calculation was also in line with classical measurements (r = 0.99, P < .001). High BMI subjects had a significantly lower 6MWD, cadence, and step length than controls (P < .001 for each). Walking speed was more closely correlated with step length (r = 0.92) than with cadence (r = 0.64) for both groups. CONCLUSION: Our results demonstrated that a ventilatory polygraph with an embedded accelerometer can be used to detect steps and U-turns, and to calculate 6MWD. This method is sufficiently sensitive to characterize significant BMI-dependent differences in gait pattern during a 6MWT and appears to be a promising tool for routine clinical use.

Validity of thoracic respiratory inductive plethysmography in high body mass index subjects.

We aim to evaluate thoracic respiratory inductive plethysmography (RIP) in high body mass index (BMI) subjects with a pneumotachometer (PT) as a reference. We simultaneously evaluated spontaneous breathing by RIP and PT in 10 low and 10 high BMI subjects at rest and in moderate exercise. We then recorded RIP amplitude with different excursions mimicking respiratory thoracic deformation, with different sizes of RIP belts surrounding cylinders of different perimeters with or without deformable foam simulating adipose tissue. RIP responses correlated with PT values in low and high BMI groups for inspiratory time (r=0.86 and r=0.91, respectively), expiratory time (r=0.96 and r=0.91, respectively) and amplitude (r=0.82 for both) but with a bias (-0.23±0.25L) for high BMI subjects. ANOVA revealed the effects of perimeter and simulated adiposity (p<0.001 for both). We concluded that thoracic perimeter and deformity of adipose tissue are responsible for biases in RIP response in high BMI subjects.

New Respiratory Inductive Plethysmography (RIP) Method for Evaluating Ventilatory Adaptation during Mild Physical Activities.

The pneumotachometer is currently the most accepted device to measure tidal breathing, however, it requires the use of a mouthpiece and thus alteration of spontaneous ventilation is implied. Respiratory inductive plethysmography (RIP), which includes two belts, one thoracic and one abdominal, is able to determine spontaneous tidal breathing without the use of a facemask or mouthpiece, however, there are a number of as yet unresolved issues. In this study we aimed to describe and validate a new RIP method, relying on a combination of thoracic RIP and nasal pressure signals taking into account that exercise-induced body movements can easily contaminate RIP thoracic signals by generating tissue motion artifacts. A custom-made time domain algorithm that relies on the elimination of low amplitude artifacts was applied to the raw thoracic RIP signal. Determining this tidal ventilation allowed comparisons between the RIP signal and simultaneously-recorded airflow signals from a calibrated pneumotachometer (PT). We assessed 206 comparisons from 30 volunteers who were asked to breathe spontaneously at rest and during walking on the spot. Comparisons between RIP signals processed by our algorithm and PT showed highly significant correlations for tidal volume (Vt), inspiratory (Ti) and expiratory times (Te). Moreover, bias calculated using the Bland and Altman method were reasonably low for Vt and Ti (0.04 L and 0.02 s, respectively), and acceptable for Te (<0.1 s) and the intercept from regression relationships (0.01 L, 0.06 s, 0.17 s respectively). The Ti/Ttot and Vt/Ti ratios obtained with the two methods were also statistically correlated. We conclude that our methodology (filtering by our algorithm and calibrating with our calibration procedure) for thoracic RIP renders this technique sufficiently accurate to evaluate tidal ventilation variation at rest and during mild to moderate physical activity.

Body Mass Index-Dependent Ventilatory Parameters From Respiratory Inductive Plethysmography During 6-Minute Walk Test.

BACKGROUND: Walking is part of obesity management. Assessment of ventilatory impairments and consequences for gait induced by obesity could be clinically helpful. We aimed to develop a method to accurately monitor ventilation with respiratory inductive plethysmography (RIP) in subjects with high body mass indices (BMIs) during a 6-min walk test (6MWT). METHODS: 25 volunteers were divided into 2 groups based on BMI (<25 or >30 kg/m2) and performed a 6MWT with a calibrated RIP. Ventilatory parameters (tidal volume [V(T)], inspiratory [T(I)] and expiratory [T(E)] times, V(T)/T(I) ratio, and T(I)/Ttot ratio) were determined after processing RIP signals with a custom-made algorithm designed to discriminate tissue motion artifacts and respiratory cycles in the time domain. Six-min walk distance and average speed by minute were collected. RESULTS: The number of artifacts removed by the algorithm used for artifact removal was higher for high-BMI subjects and was correlated to their individual values (r = 0.66, P < .001). Six-min walk distance was lower for the group with a higher BMI (P = .001). ANOVA revealed effects of exercise for V(T), T(I), and T(E) (P < .001) and also BMI effects in the course of the 6MWT for V(T), T(I), T(E), V(T)/T(I), and T(I)/Ttot (P < .001 for each of them). CONCLUSIONS: This respiratory monitoring method is sufficiently sensitive to point out differences between rest and exercise as well as locomotor and ventilatory differences relative to BMI during the 6MWT. Thus, this system gives useful information from the 6MWT for clinicians who want to assess respiratory patterns of patients during this commonly used test.