Enabling Modular Robotics with Secure Transducer Identification Based on Extended IEEE 21450 Transducer Electronic Datasheets.

In robotics, there are many different sensors and actuators mounted onto a robot which may also, in the case of modular robotics, be interchanged during operation. During development of new sensors or actuators, prototypes may also be mounted onto a robot to test functionality, where the new prototypes often have to be integrated manually into the robot environment. Proper, fast and secure identification of new sensor or actuator modules for the robot thus becomes important. In this work, a workflow to add new sensors or actuators to an existing robot environment while establishing trust in an automated manner using electronic datasheets has been developed. The new sensors or actuators are identified via near field communication (NFC) to the system and exchange security information via the same channel. By using electronic datasheets stored on the sensor or actuator, the device can be easily identified and trust can be established by using additional security information contained in the datasheet. In addition, the NFC hardware can simultaneously be used for wireless charging (WLC), thus allowing for wireless sensor and actuator modules. The developed workflow has been tested with prototype tactile sensors mounted onto a robotic gripper.

Long-term prognostic counselling in people with multiple sclerosis using an online analytical processing tool.

BACKGROUND: Prognostic counselling is a sensitive issue in medicine and especially so in MS due to the highly heterogeneous disease course. However, people with MS (pwMS) seek prognostic information. The web-based 'Evidence-Based Decision Support Tool in Multiple Sclerosis' (EBDiMS) uses data of 717 patients from the London/Ontario cohort to calculate personalized long-term prognostic information. OBJECTIVE: The aim of this study was to investigate the feasibility and effect of long-term prognostic counselling in pwMS using EBDiMS. METHODS: Ninety consecutive pwMS were provided with personalized estimations of expected time to reach Expanded Disability Status Scale (EDSS) scores of 6 and 8 and time to conversion to secondary-progressive MS. Participants gave estimates on their own putative prognosis and rated the tool's acceptability on six-step Likert-type scales. RESULTS: Participants rated EBDiMS as highly understandable, interesting and relevant for patient-physician encounters, coping and therapy decisions. Although it provoked a certain degree of worry in some participants, 95% would recommend using the tool. Participants' own prognosis estimates did not change significantly following EBDiMS. CONCLUSION: Long-term prognostic counselling using an online tool has been shown to be feasible in a clinical setting. EBDiMS provides pwMS with relevant, easy-to-understand, long-term prognostic information without causing relevant anxiety.

Correction: Long-term gait measurements in daily life: Results from the Berlin Aging Study II (BASE-II).

[This corrects the article DOI: 10.1371/journal.pone.0225026.].

Long-term gait measurements in daily life: Results from the Berlin Aging Study II (BASE-II).

BACKGROUND: Walking ability is an important prerequisite for activity, social participation and independent living. While in most healthy adults, this ability can be assumed as given, limitations in walking ability occur with increasing age. Furthermore, slow walking speed is linked to several chronic conditions and overall morbidity. Measurements of gait parameters can be used as a proxy to detect functional decline and onset of chronic conditions. Up to now, gait characteristics used for this purpose are measured in standardized laboratory settings. There is some evidence, however, that long-term measurements of gait parameters in the living environment have some advantages over short-term laboratory measurements. METHODS: We evaluated cross-sectional data from an accelerometric sensor worn in a subgroup of 554 participants of the Berlin Aging Study II (BASE-II). Data from the two BASE-II age groups (age between 22-36 years and 60-79 years) were used for the current analysis of accelerometric data for a minimum of two days and a maximum of ten days were available. Real world walking speed, number of steps, maximum coherent distance and total distance were derived as average data per day. Linear regression analyses were performed on the different gait parameters in order to identify significant determinants. Additionally, Mann-Whitney-U-tests were performed to detect sex-specific differences. RESULTS: Age showed to be significantly associated with real world walking speed and with the total distance covered per day, while BMI contributed negatively to the number of walking steps, maximum coherent distance and total distance walked. Additionally, sex was associated with walking steps. However, R2-values for all models were low. Overall, women had significantly more walking steps and a larger coherent distance per day when compared to men. When separated by age group, this difference was significant only in the older participants. Additionally, walking speed was significantly higher in women compared to men in the subgroup of older people. CONCLUSIONS: Age- and sex-specific differences have to be considered when objective gait parameters are measured, e.g. in the context of clinical risk assessment. For this purpose normative data, differentiating for age and sex would have to be established to allow reliable classification of long-term measurements of gait.

Fampridine and real-life walking in multiple sclerosis: Low predictive value of clinical test for habitual short-term changes.

BACKGROUND: Fampridine improves walking speed in patients with multiple sclerosis (MS) in performance-based tests. The impact on habitual mobility and its correlation with clinical tests has not been analysed. OBJECTIVE: To investigate the association between clinical response criteria and habitual mobility in MS patients starting a fampridine treatment. METHODS: During a four-week baseline-to-treatment study, we assessed in 28 patients (median EDSS 4.75, range 4-6.5) walking tests as the Timed-25-Foot-Walk (T25FW) and mobility questionnaires at day 0, 14 (start of treatment) and 28. Habitual steps and distance per day, total activity and walking speed was measured by accelerometry over four weeks. Beside improvement in real-life mobility, we investigated if such measures differed between non-responders and responders defined by a 20% improvement in clinical tests. RESULTS: All clinical test, patient reported outcomes and total activity improved significantly (p<0.05). 46% improved (any change >0) in three of four real-life measures. Change of the T25FW predicted only an increase of distance per day. Subjective rating of patients performed better by predicting distance and walking speed changes correctly. CONCLUSION: Fampridine might improve walking in daily life of MS, but clinical tests are weak predictors. Accelerometry opens a new perspective on mobility measurment, but the current data do not show a consistent effect on non-performance based accelerometry outcomes.

Validating predictors of disease progression in a large cohort of primary-progressive multiple sclerosis based on a systematic literature review.

BACKGROUND: New agents with neuroprotective or neuroregenerative potential might be explored in primary-progressive Multiple Sclerosis (PPMS)--the MS disease course with leading neurodegenerative pathology. Identification of patients with a high short-term risk for progression may minimize study duration and sample size. Cohort studies reported several variables as predictors of EDSS disability progression but findings were partially contradictory. OBJECTIVE: To analyse the impact of published predictors on EDSS disease progression in a large cohort of PPMS patients. METHODS: A systematic literature research was performed to identify predictors for disease progression in PPMS. Individual case data from the Sylvia Lawry Centre (SLC) and the Hamburg MS patient database (HAPIMS) was pooled for a retrospective validation of these predictors on the annualized EDSS change. RESULTS: The systematic literature analysis revealed heterogeneous data from 3 prospective and 5 retrospective natural history cohort studies. Age at onset, gender, type of first symptoms and early EDSS changes were available for validation. Our pooled cohort of 597 PPMS patients (54% female) had a mean follow-up of 4.4 years and mean change of EDSS of 0.35 per year based on 2503 EDSS assessments. There was no significant association between the investigated variables and the EDSS-change. CONCLUSION: None of the analysed variables were predictive for the disease progression measured by the annualized EDSS change. Whether PPMS is still unpredictable or our results may be due to limitations of cohort assessments or selection of predictors cannot be answered. Large systematic prospective studies with new endpoints are needed.

What is the "normal" fetal heart rate?

Aim. There is no consensus about the normal fetal heart rate. Current international guidelines recommend for the normal fetal heart rate (FHR) baseline different ranges of 110 to 150 beats per minute (bpm) or 110 to 160 bpm. We started with a precise definition of "normality" and performed a retrospective computerized analysis of electronically recorded FHR tracings. Methods. We analyzed all recorded cardiotocography tracings of singleton pregnancies in three German medical centers from 2000 to 2007 and identified 78,852 tracings of sufficient quality. For each tracing, the baseline FHR was extracted by eliminating accelerations/decelerations and averaging based on the "delayed moving windows" algorithm. After analyzing 40% of the dataset as "training set" from one hospital generating a hypothetical normal baseline range, evaluation of external validity on the other 60% of the data was performed using data from later years in the same hospital and externally using data from the two other hospitals. Results. Based on the training data set, the "best" FHR range was 115 or 120 to 160 bpm. Validation in all three data sets identified 120 to 160 bpm as the correct symmetric "normal range". FHR decreases slightly during gestation. Conclusions. Normal ranges for FHR are 120 to 160 bpm. Many international guidelines define ranges of 110 to 160 bpm which seem to be safe in daily practice. However, further studies should confirm that such asymmetric alarm limits are safe, with a particular focus on the lower bound, and should give insights about how to show and further improve the usefulness of the widely used practice of CTG monitoring.

Prognostic risk estimates of patients with multiple sclerosis and their physicians: comparison to an online analytical risk counseling tool.

BACKGROUND: Prognostic counseling in multiple sclerosis (MS) is difficult because of the high variability of disease progression. Simultaneously, patients and physicians are increasingly confronted with making treatment decisions at an early stage, which requires taking individual prognoses into account to strike a good balance between benefits and harms of treatments. It is therefore important to understand how patients and physicians estimate prognostic risk, and whether and how these estimates can be improved. An online analytical processing (OLAP) tool based on pooled data from placebo cohorts of clinical trials offers short-term prognostic estimates that can be used for individual risk counseling. OBJECTIVE: The aim of this study was to clarify if personalized prognostic information as presented by the OLAP tool is considered useful and meaningful by patients. Furthermore, we used the OLAP tool to evaluate patients' and physicians' risk estimates. Within this evaluation process we assessed short-time prognostic risk estimates of patients with MS (final n = 110) and their physicians (n = 6) and compared them with the estimates of OLAP. RESULTS: Patients rated the OLAP tool as understandable and acceptable, but to be only of moderate interest. It turned out that patients, physicians, and the OLAP tool ranked patients similarly regarding their risk of disease progression. Both patients' and physicians' estimates correlated most strongly with those disease covariates that the OLAP tool's estimates also correlated with most strongly. Exposure to the OLAP tool did not change patients' risk estimates. CONCLUSION: While the OLAP tool was rated understandable and acceptable, it was only of modest interest and did not change patients' prognostic estimates. The results suggest, however, that patients had some idea regarding their prognosis and which factors were most important in this regard. Future work with OLAP should assess long-term prognostic estimates and clarify its usefulness for patients and physicians facing treatment decisions.

Accuracy of the actibelt(®) accelerometer for measuring walking speed in a controlled environment among persons with multiple sclerosis.

BACKGROUND: Advances in portable sensor technology have opened an era for objective, real-life monitoring of walking speed in persons with multiple sclerosis (MS). PURPOSE: The present study examined the accuracy of the actibelt(®) accelerometer for measuring walking speed during a standard 6-min walk (6MW) and the possibility that disability status influenced the degree of accuracy among persons with MS. METHODS: On a single testing session, 51 persons with MS and Expanded Disability Status Scale scores between 2.0 and 6.5 performed a 6MW while wearing an actibelt(®) in the body's sagittal symmetry plane and close to the body's centre of mass. RESULTS: All 51 participants completed the 6MW without stopping, falling, or any adverse events, and the actibelt(®) provided walking speed data for each of the participants. The actibelt(®) significantly overestimated walking speed (actual minus actibelt(®)) by a mean±standard deviation of -0.12±0.17 m/s for the overall sample (p<0.0001). There was no significant overestimation in the sample with mild disability (-0.02±0.11 m/s), but there was in the samples with moderate (-0.10±0.16 m/s) and severe (-0.26±0.12 m/s) disability. CONCLUSION: The actibelt(®) is ready for real-life monitoring of walking speed in persons with mild MS, but caution is necessary when interpreting the accuracy of the walking speed data for those with MS who have moderate and severe disability.

A new method to estimate the real upper limit of the false alarm rate in a 3 accelerometry-based fall detector for the elderly.

Falls are a major concern for the elderly and their ability to remain healthy. Fall detection systems may notify emergency responders when no one apart from the injured is present. However, their real-world application is limited by a number of factors such as high false positive rates, low-compliance, poor-usability and short battery lifetime. In order to improve these aspects we have developed a miniaturized 3D accelerometer integrated in a belt buckle, the actibelt(®), and a fall detection algorithm. We have used a new evaluation method to assess the upper limit of the false alarm rate of our algorithm using a large set of long term standardized acceleration measurements recorded under real life conditions. Our algorithm has a false alarm rate of seventeen false alarms per month and has the potential to be reduced down to at most three false alarms per month when activities which require the sensor to be removed are eliminated. In laboratory settings, the algorithm has a sensitivity of 100%. The algorithm was sucessfully validated using data from a real-world fall.

Development and validation of a new method to measure walking speed in free-living environments using the actibelt® platform.

Walking speed is a fundamental indicator for human well-being. In a clinical setting, walking speed is typically measured by means of walking tests using different protocols. However, walking speed obtained in this way is unlikely to be representative of the conditions in a free-living environment. Recently, mobile accelerometry has opened up the possibility to extract walking speed from long-time observations in free-living individuals, but the validity of these measurements needs to be determined. In this investigation, we have developed algorithms for walking speed prediction based on 3D accelerometry data (actibelt®) and created a framework using a standardized data set with gold standard annotations to facilitate the validation and comparison of these algorithms. For this purpose 17 healthy subjects operated a newly developed mobile gold standard while walking/running on an indoor track. Subsequently, the validity of 12 candidate algorithms for walking speed prediction ranging from well-known simple approaches like combining step length with frequency to more sophisticated algorithms such as linear and non-linear models was assessed using statistical measures. As a result, a novel algorithm employing support vector regression was found to perform best with a concordance correlation coefficient of 0.93 (95%CI 0.92-0.94) and a coverage probability CP1 of 0.46 (95%CI 0.12-0.70) for a deviation of 0.1 m/s (CP2 0.78, CP3 0.94) when compared to the mobile gold standard while walking indoors. A smaller outdoor experiment confirmed those results with even better coverage probability. We conclude that walking speed thus obtained has the potential to help establish walking speed in free-living environments as a patient-oriented outcome measure.

Association between walking speed and age in healthy, free-living individuals using mobile accelerometry--a cross-sectional study.

CONTEXT: Walking speed is a fundamental parameter of human motion and is increasingly considered as an important indicator of individuals' health status. OBJECTIVE: To evaluate the relationship of gait parameters, and demographic and physical characteristics in healthy men and women. DESIGN, SETTING, AND PARTICIPANTS: Recruitment of a subsample (n = 358) of male and female blood donors taking part in the Cambridge CardioResource study. Collection of demographic data, measurement of physical characteristics (height, weight and blood pressure) and assessment of 7-day, free-living activity parameters using accelerometry and a novel algorithm to measure walking speed. Participants were a median (interquartile range[IQR]) age of 49 (16) years; 45% women; and had a median (IQR) BMI of 26 (5.4). MAIN OUTCOME MEASURE: Walking speed. RESULTS: In this study, the hypothesis that walking speed declines with age was generated using an initial 'open' dataset. This was subsequently validated in a separate 'closed' dataset that showed a decrease of walking speed of -0.0037 m/s per year. This is equivalent to a difference of 1.2 minutes, when walking a distance of 1 km aged 20 compared to 60 years. Associations between walking speed and other participant characteristics (i.e. gender, BMI and blood pressure) were non-significant. BMI was negatively correlated with the number of walking and running steps and longest non-stop distance. CONCLUSION: This is the first study using accelerometry which shows an association between walking speed and age in free-living, healthy individuals. Absolute values of gait speed are comparable to published normal ranges in clinical settings. This study highlights the potential use of mobile accelerometry to assess gait parameters which may be indicative of future health outcomes in healthy individuals.