Walter Christian Karlen

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Karlen

First Name

Walter Christian

ORCID

0000-0001-8643-3074

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Publications 1 - 10 of 139

Detect-and-segment: A deep learning approach to automate wound image segmentation
Scebba, Gaetano; Zhang, Jia; Catanzaro, Sabrina; et al. (2022)
Informatics in Medicine Unlocked
Chronic wounds significantly impact quality of life. They can rapidly deteriorate and require close monitoring of healing progress. Image-based wound analysis is a way of objectively assessing the wound status by quantifying important features that are related to healing. However, high heterogeneity of the wound types and imaging conditions challenge the robust segmentation of wound images. We present Detect-and-Segment (DS), a deep learning approach to produce wound segmentation maps with high generalization capabilities. In our approach, dedicated deep neural networks detected the wound position, isolated the wound from the perturbing background, and computed a wound segmentation map. We tested this approach on a diabetic foot ulcers data set and compared it to a segmentation method based on the full image. To evaluate its generalizability on out-of-distribution data, we measured the performance of the DS approach on 4 additional independent data sets, with larger variety of wound types from different body locations. The Matthews’ correlation coefficient (MCC) improved from 0.29 (full image) to 0.85 (DS) on the diabetic foot ulcer data set. When the DS was tested on the independent data sets, the mean MCC increased from 0.17 to 0.85. Furthermore, the DS enabled the training of segmentation models with up to 90% less training data without impacting the segmentation performance. The proposed DS approach is a step towards automating wound analysis and reducing efforts to manage chronic wounds.
Neuromodulation by means of phase-locked auditory stimulation affects key marker of excitability and connectivity during sleep
Sousouri, Georgia; Krugliakova, Elena; Skorucak, Jelena; et al. (2022)
Sleep
The propagating pattern of sleep slow waves (high-amplitude oscillations < 4.5 Hz) serves as a blueprint of cortical excitability and brain connectivity. Phase-locked auditory stimulation is a promising tool for the modulation of ongoing brain activity during sleep; however, its underlying mechanisms remain unknown. Here, eighteen healthy young adults were measured with high-density electroencephalography in three experimental conditions; one with no stimulation, one with up- and one with down-phase stimulation; ten participants were included in the analysis. We show that up-phase auditory stimulation on a right prefrontal area locally enhances cortical involvement and promotes traveling by increasing the propagating distance and duration of targeted small-amplitude waves. On the contrary, down-phase stimulation proves more efficient at perturbing large-amplitude waves and interferes with ongoing traveling by disengaging cortical regions and interrupting high synchronicity in the target area as indicated by increased traveling speed. These results point out different underlying mechanisms mediating the effects of up- and down-phase stimulation and highlight the strength of traveling wave analysis as a sensitive and informative method for the study of connectivity and cortical excitability alterations.
Editorial. Automation in medicine: from homecare to clinical applications
Karlen, Walter Christian; Schauer, Thomas; Möller, Knut; et al. (2018)
at - Automatisierungstechnik
A Cohort Study of Morbidity, Mortality and Health Seeking Behavior following Rural Health Center Visits by Children under 12 in Southwestern Uganda
Wiens, Matthew O.; Gan, Heng; Barigye, Celestine; et al. (2015)
PLoS ONE
Background Children discharged from hospitals in developing countries are at high risk of morbidity and mortality. However, few data describe these outcomes among children seen and discharged from rural outpatient centers. Objective The objective of this exploratory study was to identify predictors of immediate and follow-up morbidity and mortality among children visiting a rural health center in Uganda. Methods Subjects 0–12 years of age seeking care with a caregiver were consecutively enrolled from a single rural health center in Southwestern Uganda. Baseline variables were collected by research nurses and outcomes of referral, admission or death were recorded (immediate events). Death, hospital admission and health seeking occurring during the 30 days following the clinic visit were also determined (follow-up events). Univariate logistic regression was performed to identify baseline variables associated with immediate outcome and follow-up outcomes. Results Over the four-month recruitment period 717 subjects were enrolled. There were 85 (11.9%) immediate events (10.1% were admitted, 2.2% were referred, none died). Forty-seven (7.8%) events occurred within 30 days after the visit (7.3% sought care from a health provider, 1.5% were admitted and 0.5% died). Variables associated with immediate events included living more than 30 minutes from the health center, age older than 5 years, having received an antimalarial prior to the visit, having seen a community health worker prior to the visit, elevated respiratory rate or temperature, and depressed weight-for-age z score or decreased oxygen saturation. These variables were not associated with follow-up events. Conclusions Sick-child visits at a rural health center in South Western Uganda were associated with rates of mortality and subsequent admission of less than 2% in the period following the sick child visits. Other types of health seeking behavior occurred in approximately 7% of subjects during this same period. Several variables were associated with immediate events but there were no reliable predictors of follow-up events, possibly due to low statistical power.
Robot-Animal Interaction
Asadpour, Masoud; Tâche, Fabien; Caprari, Gilles; et al. (2014)
An Adaptive Single Frequency Phase Vocoder For Low-power Heart Rate Detection
Karlen, Walter Christian; Petersen, Chris; Gow, Jennifer; et al. (2011)
BIODEVICES 2011 : proceedings of the International Conference on Biomedical Electronics and Devices ; Rome, Italy, January 26 - 29, 2011
Wound Image Quality From a Mobile Health Tool for Home-Based Chronic Wound Management With Real-Time Quality Feedback: Randomized Feasibility Study
Zhang, Jia; Mihai, Carina; Tüshaus, Laura; et al. (2021)
JMIR mHealth and uHealth
Background: Travel to clinics for chronic wound management is burdensome to patients. Remote assessment and management of wounds using mobile and telehealth approaches can reduce this burden and improve patient outcomes. An essential step in wound documentation is the capture of wound images, but poor image quality can have a negative influence on the reliability of the assessment. To date, no study has investigated the quality of remotely acquired wound images and whether these are suitable for wound self-management and telemedical interpretation of wound status. Objective: Our goal was to develop a mobile health (mHealth) tool for the remote self-assessment of digital ulcers (DUs) in patients with systemic sclerosis (SSc). We aimed to define and validate objective measures for assessing the image quality, evaluate whether an automated feedback feature based on real-time assessment of image quality improves the overall quality of acquired wound images, and evaluate the feasibility of deploying the mHealth tool for home-based chronic wound self-monitoring by patients with SSc. Methods: We developed an mHealth tool composed of a wound imaging and management app, a custom color reference sticker, and a smartphone holder. We introduced 2 objective image quality parameters based on the sharpness and presence of the color checker to assess the quality of the image during acquisition and enable a quality feedback mechanism in an advanced version of the app. We randomly assigned patients with SSc and DU to the 2 device groups (basic and feedback) to self-document their DU at home over 8 weeks. The color checker detection ratio (CCDR) and color checker sharpness (CCS) were compared between the 2 groups. We evaluated the feasibility of the mHealth tool by analyzing the usability feedback from questionnaires, user behavior and timings, and the overall quality of the wound images. Results: A total of 21 patients were enrolled, of which 15 patients were included in the image quality analysis. The average CCDR was 0.96 (191/199) in the feedback group and 0.86 (158/183) in the basic group. The feedback group showed significantly higher (P<.001) CCS compared to the basic group. The usability questionnaire results showed that the majority of patients were satisfied with the tool, but could benefit from disease-specific adaptations. The median assessment duration was <50 seconds in all patients, indicating the mHealth tool was efficient to use and could be integrated into the daily routine of patients. Conclusions: We developed an mHealth tool that enables patients with SSc to acquire good-quality DU images and demonstrated that it is feasible to deploy such an app in this patient group. The feedback mechanism improved the overall image quality. The introduced technical solutions consist of a further step towards reliable and trustworthy digital health for home-based self-management of wounds.
The Performance of a Mobile Phone Respiratory Rate Counter Compared to the WHO ARI Timer
Gan, Heng; Karlen, Walter Christian; Dunsmuir, Dustin; et al. (2015)
Journal of Healthcare Engineering
OBJECTIVE: To compare the accuracy and efficiency of the respiratory rate (RR) RRate mobile application to the WHO ARI Timer. METHODS: Volunteers used both devices to measure RR from reference videos of infants and children. Measurements were compared using correlation, Bland-Altman analysis, error metrics and time taken. RESULTS: Measurements with either device were highly correlated to the reference (r = 0.991 and r = 0.982), and to each other (r = 0.973). RRate had a larger bias than the ARI Timer (0.6 vs. 0.04 br/min), but tighter limits of agreement (−4.5 to 3.3 br/min vs. −5.5 to 5.5 br/min). RRate was more accurate than the ARI Timer (percentage error 10.6% vs. 14.8%, root mean square error 2.1 vs. 2.8 br/min and normalized root mean square error 5.6% vs. 7.5%). RRate measurements were 52.7 seconds (95% CI 50.4 s to 54.9 s) faster. CONCLUSION: During video observations, RRate measured RR quicker with a similar accuracy compared to the ARI Timer.
Assessment of neonatal respiratory rate variability
Coleman, Jesse; Ginsburg, Amy Sarah; Macharia, William M.; et al. (2022)
Journal of Clinical Monitoring and Computing
Accurate measurement of respiratory rate (RR) in neonates is challenging due to high neonatal RR variability (RRV). There is growing evidence that RRV measurement could inform and guide neonatal care. We sought to quantify neonatal RRV during a clinical study in which we compared multiparameter continuous physiological monitoring (MCPM) devices. Measurements of capnography-recorded exhaled carbon dioxide across 60-s epochs were collected from neonates admitted to the neonatal unit at Aga Khan University-Nairobi hospital. Breaths were manually counted from capnograms and using an automated signal detection algorithm which also calculated mean and median RR for each epoch. Outcome measures were between- and within-neonate RRV, between- and within-epoch RRV, and 95% limits of agreement, bias, and root-mean-square deviation. Twenty-seven neonates were included, with 130 epochs analysed. Mean manual breath count (MBC) was 48 breaths per minute. Median RRV ranged from 11.5% (interquartile range (IQR) 6.8-18.9%) to 28.1% (IQR 23.5-36.7%). Bias and limits of agreement for MBC vs algorithm-derived breath count, MBC vs algorithm-derived median breath rate, MBC vs algorithm-derived mean breath rate were - 0.5 (- 2.7, 1.66), - 3.16 (- 12.12, 5.8), and - 3.99 (- 11.3, 3.32), respectively. The marked RRV highlights the challenge of performing accurate RR measurements in neonates. More research is required to optimize the use of RRV to improve care. When evaluating MCPM devices, accuracy thresholds should be less stringent in newborns due to increased RRV. Lastly, median RR, which discounts the impact of extreme outliers, may be more reflective of the underlying physiological control of breathing.
Medical Devices and Information Communication Technologies for the Base of the Pyramid
Friedman, Zach; Karlen, Walter Christian (2015)
Technologies for Development : What is Essential?

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