Monipar: movement data collection tool to monitor motor symptoms in Parkinson's disease using smartwatches and smartphones

Introduction

Parkinson's disease (PD) is a neurodegenerative disorder commonly characterized by motor impairments. The development of mobile health (m-health) technologies, such as wearable and smart devices, presents an opportunity for the implementation of clinical tools that can support tasks such as early diagnosis and objective quantification of symptoms.

Objective

This study evaluates a framework to monitor motor symptoms of PD patients based on the performance of standardized exercises such as those performed during clinic evaluation. To implement this framework, an m-health tool named Monipar was developed that uses off-the-shelf smart devices.

Methods

An experimental protocol was conducted with the participation of 21 early-stage PD patients and 7 healthy controls who used Monipar installed in off-the-shelf smartwatches and smartphones. Movement data collected using the built-in acceleration sensors were used to extract relevant digital indicators (features). These indicators were then compared with clinical evaluations performed using the MDS-UPDRS scale.

Results

The results showed moderate to strong (significant) correlations between the clinical evaluations (MDS-UPDRS scale) and features extracted from the movement data used to assess resting tremor (i.e., the standard deviation of the time series: r = 0.772, p < 0.001) and data from the pronation and supination movements (i.e., power in the band of 1-4 Hz: r = -0.662, p < 0.001).

Conclusion

These results suggest that the proposed framework could be used as a complementary tool for the evaluation of motor symptoms in early-stage PD patients, providing a feasible and cost-effective solution for remote and ambulatory monitoring of specific motor symptoms such as resting tremor or bradykinesia.

How the COVID-19 Pandemic Muted and Remixed the World's Acoustics for a While

PURPOSE OF REVIEW

This review aims to analyze the effects of the pandemic on the world's sound environment.

RECENT FINDINGS

The confinements associated with the pandemic led to a reduction in sound levels worldwide and a change in the perception of soundscapes in the absence of traffic noise and human-generated noise.

SUMMARY

In response to the COVID-19 pandemic, many countries and regions around the world adopted a series of interventions in 2020 that have been referred to as "lockdown" or "confinement." These sets of restrictions had a clear and obvious consequence derived from the absence of people in the streets and the reduction of daily activity and commuting, which caused an unprecedented silencing on a large scale. Along with the silence that ensued, the pandemic and the confinements affected acoustics and our relationship with sounds on different scales. In the cities, this phenomenon had a strong reduction in acoustic intensity due to the absence of vehicles on the streets. Perhaps this was more perceptible in our neighborhoods, with notable changes in their soundscapes, first due to the absence of people in the streets and later due to more outdoor activity derived from the fear of the spread of the virus in indoor spaces. The longer periods of time spent in our homes during the lockdowns also highlighted the importance of sound insulation in buildings and the acoustic conditioning of our schools or homes.

Automatic Resting Tremor Assessment in Parkinson's Disease Using Smartwatches and Multitask Convolutional Neural Networks

Resting tremor in Parkinson's disease (PD) is one of the most distinctive motor symptoms. Appropriate symptom monitoring can help to improve management and medical treatments and improve the patients' quality of life. Currently, tremor is evaluated by physical examinations during clinical appointments; however, this method could be subjective and does not represent the full spectrum of the symptom in the patients' daily lives. In recent years, sensor-based systems have been used to obtain objective information about the disease. However, most of these systems require the use of multiple devices, which makes it difficult to use them in an ambulatory setting. This paper presents a novel approach to evaluate the amplitude and constancy of resting tremor using triaxial accelerometers from consumer smartwatches and multitask classification models. These approaches are used to develop a system for an automated and accurate symptom assessment without interfering with the patients' daily lives. Results show a high agreement between the amplitude and constancy measurements obtained from the smartwatch in comparison with those obtained in a clinical assessment. This indicates that consumer smartwatches in combination with multitask convolutional neural networks are suitable for providing accurate and relevant information about tremor in patients in the early stages of the disease, which can contribute to the improvement of PD clinical evaluation, early detection of the disease, and continuous monitoring.

Changes in noise levels in the city of Madrid during COVID-19 lockdown in 2020

The lockdown that Madrid has suffered during the months of March to June 2020 to try to control and minimize the spread of COVID-19 has significantly altered the acoustic environment of the city. The absence of vehicles and people on the streets has led to a noise reduction captured by the monitoring network of the City of Madrid. In this article, an analysis has been carried out to describe the reduction in noise pollution that has occurred and to analyze the changes in the temporal patterns of noise, which are strongly correlated with the adaptation of the population's activity and behavior to the new circumstances. The reduction in the sound level ranged from 4 to 6 dBA for the indicators Ld, Le, and Ln, and this is connected to a significant variation in the daily time patterns, especially during weekends, when the activity started earlier in the morning and lasted longer at midday, decreasing significantly in the afternoon.

Deep Learning Approaches for Detecting Freezing of Gait in Parkinson's Disease Patients through On-Body Acceleration Sensors

Freezing of gait (FOG) is one of the most incapacitating motor symptoms in Parkinson's disease (PD). The occurrence of FOG reduces the patients' quality of live and leads to falls. FOG assessment has usually been made through questionnaires, however, this method can be subjective and could not provide an accurate representation of the severity of this symptom. The use of sensor-based systems can provide accurate and objective information to track the symptoms' evolution to optimize PD management and treatments. Several authors have proposed specific methods based on wearables and the analysis of inertial signals to detect FOG in laboratory conditions, however, its performance is usually lower when being used at patients' homes. This study presents a new approach based on a recurrent neural network (RNN) and a single waist-worn triaxial accelerometer to enhance the FOG detection performance to be used in real home-environments. Also, several machine and deep learning approaches for FOG detection are evaluated using a leave-one-subject-out (LOSO) cross-validation. Results show that modeling spectral information of adjacent windows through an RNN can bring a significant improvement in the performance of FOG detection without increasing the length of the analysis window (required to using it as a cue-system).

On the Person-Place Interaction and Its Relationship with the Responses/Outcomes of Listeners of Urban Soundscape (Compared Cases of Lisbon and Bogotá): Contextual and Semiotic Aspects

Design, planning, and management of the urban soundscape require various interacting fields of knowledge given the fact that it is the human person that experiences and provides meaning to the urban places and their acoustic environments. The process of environmental perception involves contextual information that conditions people’s responses and outcomes through the relationship between the variables Person, Activity, and Place. This research focuses on the interaction between Person and Place and its impact on responses and outcomes from listeners with different geographical origin and background. Laboratory studies were conducted in the cities of Lisbon (Portugal) and Bogotá (Colombia), where local listeners were introduced to known and unknown acoustic environments. Sound data recorded in the two cities allowed comparison of responses and outcomes of the listeners according to the Person-Place Interaction, leading to different meanings depending on the contextual variables. The results clearly show a relationship between site, acoustic environment, soundscape, Person-Place Interaction, and meaning of the place. This information can be useful for urban technicians and designers dealing with planning and management of urban soundscapes.

Occupational Risk Prevention through Smartwatches: Precision and Uncertainty Effects of the Built-In Accelerometer

Wearable technology has had a significant growth in the last years; this is particularly true of smartwatches, due to their potential advantages and ease of use. These smart devices integrate sensors that can be potentially used within industrial settings and for several applications, such as safety, monitoring, and the identification of occupational risks. The accelerometer is one of the main sensors integrated into these devices. However, several studies have identified that sensors integrated into smart devices may present inaccuracies during data acquisition, which may influence the performance of their potential applications. This article presents an analysis from the metrological point of view to characterize the amplitude and frequency response of the integrated accelerometers in three currently available commercial smartwatches, and it also includes an analysis of the uncertainties associated with these measurements by adapting the procedures described in several International Organization for Standardization (ISO) standards. The results show that despite the technical limitations produced by the factory configuration, these devices can be used in various applications related to occupational risk assessment. Opportunities for improvement have also been identified, which will allow us to take advantage of this technology in several innovative applications within industrial settings and, in particular, for occupational health purposes.

Pegvisomant and cabergoline combination therapy in acromegaly

Combination with cabergoline may offer additional benefits to acromegalic patients on pegvisomant monotherapy. We evaluated the safety and efficacy profile of this combination and investigated the determinants of response. An observational, retrospective, cross-sectional study. Fourteen acromegalic patients (9 females), who were partially resistant to somatostatin analogs and on pegvisomant monotherapy. Cabergoline was added because of the presence of persistent mildly increased IGF-I. The mean follow-up time was 18.3 ± 10.4 months. The efficacy and safety profile was assessed. The influence of clinical and biochemical characteristics on treatment efficacy was studied. IGF-I levels returned to normal in 4 patients (28%) at the end of the study. In addition, some decline in IGF-I levels was observed in a further 5 patients. The % IGF-I decreased from 158 ± 64% to 124 ± 44% (p = 0.001). The average change in IGF-I was -18 ± 27% (range -67 to +24%). Lower baseline IGF-I (p = 0.007), female gender (p = 0.013), lower body weight (p = 0.031), and higher prolactin (PRL) levels (p = 0.007) were associated with a better response to combination therapy. There were no significant severe adverse events. Significant tumour shrinkage was observed in 1 patient. Combination therapy with pegvisomant and cabergoline could provide better control of IGF-I in some patients with acromegaly. Baseline IGF-I levels, female gender, body weight, and PRL levels affect the response to this combination therapy.

Assessment of noise exposure during commuting in the Madrid subway

Because noise-induced hearing impairment is the result not only of occupational noise exposure but also of total daily noise exposure, it is important to take the non-occupational exposure of individuals (during commuting to and from their jobs, at home, and during recreational activities) into account. Mass transit is one of the main contributors to non-occupational noise exposure. We developed a new methodology to estimate a representative commuting noise exposure. The methodology was put into practice for the Madrid subway because of all Spanish subway systems it covers the highest percentage of worker journeys (22.6%). The results of the application highlight that, for Madrid subway passengers, noise exposure level normalized to a nominal 8 hr (L(Ex,8h-cj) ) depends strongly on the type of train, the presence of squealing noise, and the public address audio system, ranging from 68.6 dBA to 72.8 dBA. These values play an important role in a more complete evaluation of a relationship between noise dose and worker health response.

Reduction in Calculated Uncertainty of a Noise Map by Improving the Traffic Model Data Through Two Phases

The influence of applying European default traffic values to the making of a noise map was evaluated in a typical environment like Palma de Mallorca. To assess these default traffic values, a first model has been created and compared with measured noise levels. Subsequently a second traffic model, improving the input data used for the first one, has been created and validated according to the deviations. Different methodologies were also examined for collecting model input data that would be of higher quality, by analysing the improvement generated in the reduction in the uncertainty of the noise map introduced by the road traffic noise emission.

Normal calcitonin response to pentagastrin stimulation in patients with chronic renal failure

High calcitonin levels have been reported in chronic renal failure. To study the C cell response in patients with chronic renal failure, an intravenous bolus of pentagastrin was administered to 11 patients and 11 healthy subjects. Samples were obtained at 0, 1, 2, 3, 5 and 10 min for calcitonin assay. In order to detect only the active monomeric calcitonin, an immunoradiometric assay method was used. The influence of calcium, phosphate, alkaline phosphatase and intact parathyroid hormone was also evaluated. Although basal calcitonin levels were higher (p < 0.01) in chronic renal failure (mean +/- SEM: 10.1 +/- 2.9 pmol/l) versus healthy subjects (1.1 +/- 0.3 pmol/l), the area under the curve showed there to be no differences between the two groups. The rising branch of the area under the curve, employed as an expression of the C cell response capacity, showed no differences either (chronic renal failure vs healthy subjects: 5.6 +/- 2 vs 2.6 +/- 0.7 pmol l-1 min-1, p = 0.28). In the chronic renal failure group, a positive correlation was found (r = 0.625, p < 0.05) between the rising branch of the area under the curve and parathyroid hormone. We conclude that monomeric calcitonin is increased in chronic renal failure, but C cells of the thyroid respond to pentagastrin, as they do in normal subjects. This finding is of great clinical importance when a patient with renal impairment is evaluated for medullary thyroid carcinoma. The calcitonin response to pentagastrin seems to be related directly to the degree of secondary hyperparathyroidism in chronic renal failure.