Discriminating Between Indoor and Outdoor Environments During Daily Living Activities Using Local Magnetic Field Characteristics and Machine Learning Techniques

Wearable technology has rapidly advanced, opening new possibilities for context-aware applications in fields such as healthcare and gait analysis, where distinguishing between indoor and outdoor environments is essential. This is often accomplished through technologies like GPS, Wi-Fi, cellular, and Bluetooth which, however, come with privacy concerns, high power consumption, and dependency on external infrastructure. To address these challenges, recent studies have preliminary exploited the ambient magnetic field, though comprehensive validation with real-life data is lacking. This paper seeks to validate machine learning techniques, i.e., random forest, extreme gradient boosting, and stacked long short-term memory networks, for indoor-outdoor discrimination using exclusively magnetometer data from the daily activities of 20 participants in four cities across three countries. The study investigated the most effective magnetometer placement (feet, lower back, and non-dominant wrist) and pre-processing techniques (e.g., features and window size). Reference data is obtained through a GPS-based algorithm coupled with a geographical database running on a smartphone. The extreme gradient boosting algorithm yielded the best results, with an accuracy of 0.91, an F1-score of 0.90, and an area under the ROC curve of 0.94. These findings confirm the feasibility of accurately estimating indoor/outdoor context information from magnetometer at the same update frequency of a common GPS, but with an important energy savings. The proposed model can be integrated into state-of-the-art gait analysis systems, being able to discriminate the location to avoid misinterpreting gait deviations in real-world settings, thus supporting continuous and ubiquitous gait monitoring. Datasets and algorithm implementations have been made publicly available

Upregulation of PKD1L2 provokes a complex neuromuscular disease in the mouse

Following a screen for neuromuscular mouse mutants, we identified ostes, a novel N-ethyl N-nitrosourea-induced mouse mutant with muscle atrophy. Genetic and biochemical evidence shows that upregulation of the novel, uncharacterized transient receptor potential polycystic (TRPP) channel PKD1L2 (polycystic kidney disease gene 1-like 2) underlies this disease. Ostes mice suffer from chronic neuromuscular impairments including neuromuscular junction degeneration, polyneuronal innervation and myopathy. Ectopic expression of PKD1L2 in transgenic mice reproduced the ostes myopathic changes and, indeed, caused severe muscle atrophy in Tg(Pkd1l2)/Tg(Pkd1l2) mice. Moreover, double-heterozygous mice (ostes/+, Tg(Pkd1l2)/0) suffer from myopathic changes more profound than each heterozygote, indicating positive correlation between PKD1L2 levels and disease severity. We show that, in vivo, PKD1L2 primarily associates with endogenous fatty acid synthase in normal skeletal muscle, and these proteins co-localize to costameric regions of the muscle fibre. In diseased ostes/ostes muscle, both proteins are upregulated, and ostes/ostes mice show signs of abnormal lipid metabolism. This work shows the first role for a TRPP channel in neuromuscular integrity and disease

Technical validation of real-world monitoring of gait: a multicentric observational study

Introduction: Existing mobility endpoints based on functional performance, physical assessments and patient self-reporting are often affected by lack of sensitivity, limiting their utility in clinical practice. Wearable devices including inertial measurement units (IMUs) can overcome these limitations by quantifying digital mobility outcomes (DMOs) both during supervised structured assessments and in real-world conditions. The validity of IMU-based methods in the real- world, however, is still limited in patient populations. Rigorous validation procedures should cover the device metrological verification, the validation of the algorithms for the DMOs computation specifically for the population of interest and in daily life situations, and the users’ perspective on the device. Methods and analysis: This protocol was designed to establish the technical validity and patient acceptability of the approach used to quantify digital mobility in the real world by Mobilise-D, a consortium funded by the European Union (EU) as part of the Innovative Medicine Initiative, aiming at fostering regulatory approval and clinical adoption of DMOs. After defining the procedures for the metrological verification of an IMU-based device, the experimental procedures for the validation of algorithms used to calculate the DMOs are presented. These include laboratory and real-world assessment in 120 participants from five groups: healthy older adults; chronic obstructive pulmonary disease, Parkinson’s disease, multiple sclerosis, proximal femoral fracture and congestive heart failure. DMOs extracted from the monitoring device will be compared with those from different reference systems, chosen according to the contexts of observation. Questionnaires and interviews will evaluate the users’ perspective on the deployed technology and relevance of the mobility assessment. Ethics and dissemination: The study has been granted ethics approval by the centre’s committees (London—Bloomsbury Research Ethics committee; Helsinki Committee, Tel Aviv Sourasky Medical Centre; Medical Faculties of The University of Tübingen and of the University of Kiel). Data and algorithms will be made publicly available

Translating digital healthcare to enhance clinical management: a protocol for an observational study using a digital health technology system to monitor medication adherence and its effect on mobility in people with Parkinson’s

Introduction In people with Parkinson’s (PwP) impaired mobility is associated with an increased falls risk. To improve mobility, dopaminergic medication is typically prescribed, but complex medication regimens result in suboptimal adherence. Exploring medication adherence and its impact on mobility in PwP will provide essential insights to optimise medication regimens and improve mobility. However, this is typically assessed in controlled environments, during one-off clinical assessments. Digital health technology (DHT) presents a means to overcome this, by continuously and remotely monitoring mobility and medication adherence. This study aims to use a novel DHT system (DHTS) (comprising of a smartphone, smartwatch and inertial measurement unit (IMU)) to assess self-reported medication adherence, and its impact on digital mobility outcomes (DMOs) in PwP.Methods and analysis This single-centre, UK-based study, will recruit 55 participants with Parkinson’s. Participants will complete a range of clinical, and physical assessments. Participants will interact with a DHTS over 7 days, to assess self-reported medication adherence, and monitor mobility and contextual factors in the real world. Participants will complete a motor complications diary (ON-OFF-Dyskinesia) throughout the monitoring period and, at the end, a questionnaire and series of open-text questions to evaluate DHTS usability. Feasibility of the DHTS and the motor complications diary will be assessed. Validated algorithms will quantify DMOs from IMU walking activity. Time series modelling and deep learning techniques will model and predict DMO response to medication and effects of contextual factors. This study will provide essential insights into medication adherence and its effect on real-world mobility in PwP, providing insights to optimise medication regimens.Ethics and dissemination Ethical approval was granted by London—142 Westminster Research Ethics Committee (REC: 21/PR/0469), protocol V.2.4. Results will be published in peer-reviewed journals. All participants will provide written, informed consent.Trial registration number ISRCTN13156149

Feasibility and usability of a digital health technology system to monitor mobility and assess medication adherence in mild-to-moderate Parkinson's disease

IntroductionParkinson's disease (PD) is a neurodegenerative disorder which requires complex medication regimens to mitigate motor symptoms. The use of digital health technology systems (DHTSs) to collect mobility and medication data provides an opportunity to objectively quantify the effect of medication on motor performance during day-to-day activities. This insight could inform clinical decision-making, personalise care, and aid self-management. This study investigates the feasibility and usability of a multi-component DHTS to remotely assess self-reported medication adherence and monitor mobility in people with Parkinson's (PwP).MethodsThirty participants with PD [Hoehn and Yahr stage I (n = 1) and II (n = 29)] were recruited for this cross-sectional study. Participants were required to wear, and where appropriate, interact with a DHTS (smartwatch, inertial measurement unit, and smartphone) for seven consecutive days to assess medication adherence and monitor digital mobility outcomes and contextual factors. Participants reported their daily motor complications [motor fluctuations and dyskinesias (i.e., involuntary movements)] in a diary. Following the monitoring period, participants completed a questionnaire to gauge the usability of the DHTS. Feasibility was assessed through the percentage of data collected, and usability through analysis of qualitative questionnaire feedback.ResultsAdherence to each device exceeded 70% and ranged from 73 to 97%. Overall, the DHTS was well tolerated with 17/30 participants giving a score > 75% [average score for these participants = 89%, from 0 (worst) to 100 (best)] for its usability. Usability of the DHTS was significantly associated with age (ρ = −0.560, BCa 95% CI [−0.791, −0.207]). This study identified means to improve usability of the DHTS by addressing technical and design issues of the smartwatch. Feasibility, usability and acceptability were identified as key themes from PwP qualitative feedback on the DHTS.ConclusionThis study highlighted the feasibility and usability of our integrated DHTS to remotely assess medication adherence and monitor mobility in people with mild-to-moderate Parkinson's disease. Further work is necessary to determine whether this DHTS can be implemented for clinical decision-making to optimise management of PwP

Data_Sheet_2_Feasibility and usability of a digital health technology system to monitor mobility and assess medication adherence in mild-to-moderate Parkinson's disease.PDF

IntroductionParkinson's disease (PD) is a neurodegenerative disorder which requires complex medication regimens to mitigate motor symptoms. The use of digital health technology systems (DHTSs) to collect mobility and medication data provides an opportunity to objectively quantify the effect of medication on motor performance during day-to-day activities. This insight could inform clinical decision-making, personalise care, and aid self-management. This study investigates the feasibility and usability of a multi-component DHTS to remotely assess self-reported medication adherence and monitor mobility in people with Parkinson's (PwP).MethodsThirty participants with PD [Hoehn and Yahr stage I (n = 1) and II (n = 29)] were recruited for this cross-sectional study. Participants were required to wear, and where appropriate, interact with a DHTS (smartwatch, inertial measurement unit, and smartphone) for seven consecutive days to assess medication adherence and monitor digital mobility outcomes and contextual factors. Participants reported their daily motor complications [motor fluctuations and dyskinesias (i.e., involuntary movements)] in a diary. Following the monitoring period, participants completed a questionnaire to gauge the usability of the DHTS. Feasibility was assessed through the percentage of data collected, and usability through analysis of qualitative questionnaire feedback.ResultsAdherence to each device exceeded 70% and ranged from 73 to 97%. Overall, the DHTS was well tolerated with 17/30 participants giving a score > 75% [average score for these participants = 89%, from 0 (worst) to 100 (best)] for its usability. Usability of the DHTS was significantly associated with age (ρ = −0.560, BCa 95% CI [−0.791, −0.207]). This study identified means to improve usability of the DHTS by addressing technical and design issues of the smartwatch. Feasibility, usability and acceptability were identified as key themes from PwP qualitative feedback on the DHTS.ConclusionThis study highlighted the feasibility and usability of our integrated DHTS to remotely assess medication adherence and monitor mobility in people with mild-to-moderate Parkinson's disease. Further work is necessary to determine whether this DHTS can be implemented for clinical decision-making to optimise management of PwP.</p

Data_Sheet_1_Feasibility and usability of a digital health technology system to monitor mobility and assess medication adherence in mild-to-moderate Parkinson's disease.PDF

IntroductionParkinson's disease (PD) is a neurodegenerative disorder which requires complex medication regimens to mitigate motor symptoms. The use of digital health technology systems (DHTSs) to collect mobility and medication data provides an opportunity to objectively quantify the effect of medication on motor performance during day-to-day activities. This insight could inform clinical decision-making, personalise care, and aid self-management. This study investigates the feasibility and usability of a multi-component DHTS to remotely assess self-reported medication adherence and monitor mobility in people with Parkinson's (PwP).MethodsThirty participants with PD [Hoehn and Yahr stage I (n = 1) and II (n = 29)] were recruited for this cross-sectional study. Participants were required to wear, and where appropriate, interact with a DHTS (smartwatch, inertial measurement unit, and smartphone) for seven consecutive days to assess medication adherence and monitor digital mobility outcomes and contextual factors. Participants reported their daily motor complications [motor fluctuations and dyskinesias (i.e., involuntary movements)] in a diary. Following the monitoring period, participants completed a questionnaire to gauge the usability of the DHTS. Feasibility was assessed through the percentage of data collected, and usability through analysis of qualitative questionnaire feedback.ResultsAdherence to each device exceeded 70% and ranged from 73 to 97%. Overall, the DHTS was well tolerated with 17/30 participants giving a score > 75% [average score for these participants = 89%, from 0 (worst) to 100 (best)] for its usability. Usability of the DHTS was significantly associated with age (ρ = −0.560, BCa 95% CI [−0.791, −0.207]). This study identified means to improve usability of the DHTS by addressing technical and design issues of the smartwatch. Feasibility, usability and acceptability were identified as key themes from PwP qualitative feedback on the DHTS.ConclusionThis study highlighted the feasibility and usability of our integrated DHTS to remotely assess medication adherence and monitor mobility in people with mild-to-moderate Parkinson's disease. Further work is necessary to determine whether this DHTS can be implemented for clinical decision-making to optimise management of PwP.</p

Data_Sheet_3_Feasibility and usability of a digital health technology system to monitor mobility and assess medication adherence in mild-to-moderate Parkinson's disease.xlsx

IntroductionParkinson's disease (PD) is a neurodegenerative disorder which requires complex medication regimens to mitigate motor symptoms. The use of digital health technology systems (DHTSs) to collect mobility and medication data provides an opportunity to objectively quantify the effect of medication on motor performance during day-to-day activities. This insight could inform clinical decision-making, personalise care, and aid self-management. This study investigates the feasibility and usability of a multi-component DHTS to remotely assess self-reported medication adherence and monitor mobility in people with Parkinson's (PwP).MethodsThirty participants with PD [Hoehn and Yahr stage I (n = 1) and II (n = 29)] were recruited for this cross-sectional study. Participants were required to wear, and where appropriate, interact with a DHTS (smartwatch, inertial measurement unit, and smartphone) for seven consecutive days to assess medication adherence and monitor digital mobility outcomes and contextual factors. Participants reported their daily motor complications [motor fluctuations and dyskinesias (i.e., involuntary movements)] in a diary. Following the monitoring period, participants completed a questionnaire to gauge the usability of the DHTS. Feasibility was assessed through the percentage of data collected, and usability through analysis of qualitative questionnaire feedback.ResultsAdherence to each device exceeded 70% and ranged from 73 to 97%. Overall, the DHTS was well tolerated with 17/30 participants giving a score > 75% [average score for these participants = 89%, from 0 (worst) to 100 (best)] for its usability. Usability of the DHTS was significantly associated with age (ρ = −0.560, BCa 95% CI [−0.791, −0.207]). This study identified means to improve usability of the DHTS by addressing technical and design issues of the smartwatch. Feasibility, usability and acceptability were identified as key themes from PwP qualitative feedback on the DHTS.ConclusionThis study highlighted the feasibility and usability of our integrated DHTS to remotely assess medication adherence and monitor mobility in people with mild-to-moderate Parkinson's disease. Further work is necessary to determine whether this DHTS can be implemented for clinical decision-making to optimise management of PwP.</p

Mechanism of Regulation of bcl-2 mRNA by Nucleolin and A+U-rich Element-binding Factor 1 (AUF1)*

The antiapoptotic Bcl-2 protein is overexpressed in a variety of cancers, particularly leukemias. In some cell types this is the result of enhanced stability of bcl-2 mRNA, which is controlled by elements in its 3′-untranslated region. Nucleolin is one of the proteins that binds to bcl-2 mRNA, thereby increasing its half-life. Here, we examined the site on the bcl-2 3′-untranslated region that is bound by nucleolin as well as the protein binding domains important for bcl-2 mRNA recognition. RNase footprinting and RNA fragment binding assays demonstrated that nucleolin binds to a 40-nucleotide region at the 5′ end of the 136-nucleotide bcl-2 AU-rich element (AREbcl-2). The first two RNA binding domains of nucleolin were sufficient for high affinity binding to AREbcl-2. In RNA decay assays, AREbcl-2 transcripts were protected from exosomal decay by the addition of nucleolin. AUF1 has been shown to recruit the exosome to mRNAs. When MV-4-11 cell extracts were immunodepleted of AUF1, the rate of decay of AREbcl-2 transcripts was reduced, indicating that nucleolin and AUF1 have opposing roles in bcl-2 mRNA turnover. When the function of nucleolin in MV-4-11 cells was impaired by treatment with the nucleolin-targeting aptamer AS1411, association of AUF1 with bcl-2 mRNA was increased. This suggests that the degradation of bcl-2 mRNA induced by AS1411 results from both interference with nucleolin protection of bcl-2 mRNA and recruitment of the exosome by AUF1. Based on our findings, we propose a model that illustrates the opposing roles of nucleolin and AUF1 in regulating bcl-2 mRNA stability