Madelyn Yiseth

Rojas Castro

Ludivine Orriols

Dunia Basha Sakr

Benjamin Contrand

Marion Dupuy

Marina Travanca

Catherine Sztal-Kutas

Marta Avalos

Emmanuel Lagarde
email: emmanuel.lagarde@u-bordeaux.fr

A web-based prospective cohort study of home, leisure, school and sports injuries in France: a descriptive analysis

Keywords: Wounds and injuries, Safety, Home accident, Falls, Prospective studies

Background: Home and leisure injuries (HLIs) are a major public health problem. Cohort studies among general population are needed for targeted preventive actions but remain scarce. We quantify and qualify the HLIs collected prospectively in the MAVIE (Mutualists against Home and Leisure Injuries) observatory, a web-based cohort among volunteers of the French general population.

Methods: Participants reported HLIs from November 2014 to December 2019. We calculated crude and standardized incidence rates (SIRs) on the entire cohort, for each of the selected socio-demographic variables and each of the injury circumstances (place and activity), mechanisms, and injury severity levels. We also described other HLIs characteristics and consequences. Results: Out of the 29,931 household members enrolled in the cohort, 12,419 participants completed the questionnaires. Among them, 8640 participants provided follow-up data, leading to a follow-up of 6302 persons for 5.2 years and 2483 HLIs were reported. We obtained a SIR of 85.0 HLIs per 1000 persons-years. Most reported injuries did not require emergency department attendance or hospitalization (64%). SIRs were higher in children (< 15 years of age) (109.1 HLIs per 1000 persons-years; 95% CI, 78.2-140.1) and adults aged 70 years and older (123.7 HLIs per 1000 persons-years; 95% CI, 79.2-168.3). Struck or hit by fall was the most frequent injury mechanism (52%) and also among the most severe injuries (73% of Struck or hit by fall HLIs ending with hospitalization). Sport (without contact with nature), and leisure and play activities were the injury circumstances with higher SIRs, 15.2 HLIs per 1000 persons-years (95% CI, 14.6-15.8) and 11.2 HLIs per 1000 persons-years (95% CI, 10.7-11.6), respectively. Outdoor sport activity (in contact with nature) was the circumstance with the highest proportion of hospitalizations (18% of outdoor sports HLIs ending with hospitalization).

Conclusion:

The incidences, causes, and consequences of HLI differ by age group and are mainly related to the performance of certain activities. Although the participants in the MAVIE cohort were not representative of the French population. Our study identified potential sub-populations and specific types of HLIs that should be targeted by future studies concerning risk factors and prevention programs.

Background

Home Leisure Injuries (HLIs) refer to a wide range of events occurring at any time in private life (including also sport and school injuries), except injuries due to road traffic injuries, occupational injuries, suicide, violence, or aggression. HLIs are a substantial cause of mortality, morbidity and an important contributor to health costs. In 2017, according to estimates from the Global Burden of Disease Study, 415 million people suffered unintentional injuries (excluding road traffic injuries), and 1.8 million died [START_REF] Roser | Burden of Disease. Our World Data[END_REF]. HLIs were the most frequent type of unintentional injury.

In 26 countries of the European Union (EU), there are 25 million people attending the emergency departments (EDs) every year, and 113 thousand people die due to HLIs [START_REF] Eurosafe | Injuries in the European Union. Summary of injury statistics for the years 2012-2014[END_REF]. Between 2013 and 2016, falls were the leading cause of fatal injuries (22%), followed by road traffic injuries (13%), poisonings (10%), cuts and piercings (4%), and burns and scalds (2%) [START_REF] Eurosafe | Injuries in the European Union. Summary of injury statistics for the years 2012-2014[END_REF]. The burden of injuries is unevenly distributed among populations, areas and countries and depends on the steepness of the social gradient, health status, lifestyle and local policies [START_REF] Zambon | Injuries and inequities guidance for addressing inequities in unintentional injuries (OMS)[END_REF][START_REF] Stewart | Unintentional injuries: magnitude, prevention, and control[END_REF][START_REF] Polinder | Assessing the burden of injury in six European countries[END_REF][START_REF] Smith | Unintentional injuries in developing countries: the epidemiology of a neglected problem[END_REF].

Successful preventive interventions require the availability of HLIs data at all levels. Injury Surveillance Systems based on ED attendance and hospitalization data are the primary sources. In the United States, a valuable source is the National Electronic Injury Surveillance System that collects ED attendance information related to consumer products (Consumer Product Safety Commission) (U.S. Consumer Product Safety Commission, 1977). In Canada, the Canadian Hospitals Injury Reporting and Prevention Program provides information on injury circumstances in some pediatric and general hospitals [START_REF] Mackenzie | CHIRPP: Canada's principal injury surveillance program[END_REF]. In the EU, the association EuroSafe (European Association for Injury Prevention and Safety Promotion) aggregates data from member countries into the EU-Injury Database [START_REF] Lyons | EU-Injury Database: Operating Manual-version[END_REF]. In France, the French Home and Leisure Injury Permanent Survey (Enquête Permanente sur les Accidents de la vie Courante -EPAC) is the primary HLIs data source. It has been in operation since 2000, with a sample of 20 thousand HLIs every year (Institut de veille sanitaire, 2005). Other HLIs sources of data are mortality registers and specific population health surveys, as the Health, Health Care and Insurance Survey (l'Enquête Santé et Protection Sociale -ESPS) [START_REF] Paget | Les accidents de la vie courante en France Métropolitaine selon l'enquete santé et protection sociale 2012[END_REF].

In spite of the availability of surveillance systems, preventive actions are hampered by the lack of knowledge of exposure factors and information on the characteristics of individual vulnerabilities. Longitudinal data are needed to explore the association of emerging factors.

So far, studies with regard to the HLIs in the general population are scarce; existing cohort studies focus mainly on children and young adults [START_REF] Zonfrillo | A Systematic Review of Longitudinal Cohort Studies Examining Unintentional Injury in Young Children[END_REF], sports injuries [START_REF] Van Der Worp | Injuries in runners; a systematic review on risk factors and sex differences[END_REF], and falls in older adults [START_REF] Ho | Incidence and prevalence of falls in adults with intellectual disability living in the community: a systematic review[END_REF]. Finally, there are limited data on the epidemiology of HLIs and different severity levels of the injuries: hospitalization, ED attendance, or simple medical care.

In response to these challenges, we developed a cohort study in France, i.e., the Mutualists against Home and Leisure Injuries observatory (Mutualistes pour la recherche contre les Accidents de la VIE courante -MAVIE), intending to survey HLIs of any severity level and to elucidate the most relevant exposures and risk factors. We describe in this article the incidences, circumstances, mechanisms, consequences, and other characteristics of the injury events collected from the MAVIE cohort.

Methods

Aim, design and setting of the study

The MAVIE observatory is a web-based prospective cohort study, with a longitudinal follow-up of HLIs [START_REF] Rojas-Castro | Cohort profile: MAVIE a web-based prospective cohort study of home, leisure, and sports injuries in France[END_REF]. All households in France and in French overseas territories were eligible to participate. The recruitment process began in November 2014 and is still ongoing. This article analyzes the information collected up to 31 December 2019.

Cohort management was entirely online, including invitations, registration, and data collection. The largest share of participants was recruited through an email invitation sent to their insurees by three mutual insurance companies (MAAF, MACIF, and MAIF). A smaller proportion of the participants was informed of the MAVIE observatory and invited to participate through press releases, social media, posters, flyers, and material incentives.

Potential participants are asked to choose a household reference member, who receives all correspondence and reminder messages and is in charge of reporting HLIs that may happen to any consenting household members. Each member was free to participate or not and had to provide individual consent.

The inclusion criteria were: 1) residing in France, 2) being able to answer the questionnaires in French, 3) having access to and being able to use the Internet (at least the reference member). In an attempt to address the foreseeable underrepresentation of older participants who may have difficulties using computers, another participation status was created for caregivers whose only role is to represent older persons. It was also possible to participate to represent a child. We describe other attempts to reduce bias in the MAVIE observatory in elsewhere [START_REF] Rojas-Castro | Cohort profile: MAVIE a web-based prospective cohort study of home, leisure, and sports injuries in France[END_REF].

Data collection

Adults who signed a consent form to participate in the study by themselves or their children were asked to complete several web-based questionnaires. These inclusion questionnaires were designed to collect information including, socio-demographic characteristics, health, domestic, sport and leisure activities, lifestyles, and the home characteristics of each participants.

Follow-up

Events could be reported at any time on the website. In addition, every three months, the reference member received a reminder email to invite him/her to report any injury events that may have happened to any participant members of the household. If no event had occurred, a link in the email made it possible to report with a single click. Injury-reporting questionnaire collects information on the circumstances of occurrence (the main activity and place for each injury event), the multiple mechanisms (such as impact, crushing and cutting), the type of medical care, the typology of injury (fracture, contusion), the injury body location, limitations on doing usual activities for the 48 h following the event and the total number of lost work/study days and. Injury variables were coded using the same format as that developed for the EU-Injury database and the EPAC survey [START_REF] Thélot | Guide de référence pour le recueil des données de l'Enquête permanente sur les accidents de la vie courante[END_REF].

Participant data

We considered as participants all the household members reported by the reference member who agreed to participate in the study. The baseline sample was defined as participants who gave an answer to at least one question in the individual inclusion questionnaire. Additionally, we defined a follow-up sample as people who reported at least one news statement to the cohort.

HLI data

We excluded all clearly identifiable, all events involving illness, medical symptoms, and all reported events during which no injury was sustained, or that concerned someone other than the participant. In order to fulfil the definition of HLI, we excluded all road or occupational injuries that may have been mistakenly reported. Finally, all iatrogenic events were excluded. We excluded events that occurred before the entry into the study and those that were reported on the same date as the consent date. Finally, injuries were only included when information about the type of medical care, mechanism, place or activity were reported.

Statistical analysis

Data were analyzed using R 3.6.1 (R Development Core Team, n.d.). We considered the follow-up time from the consent date to: the last news statement date, or the questionnaires update date. If the participant asked to leave the study, we used the cohort exit date or the date of death, if reported. In an attempt to evaluate the completeness of the cohort follow-up, we computed the Person-Time Follow-up Rate (PTFR), which consists of the observed person-time (until the last news statement date) divided by the total person-time assuming no dropouts (time from the consent date to the cut-off date) [START_REF] Xue | New methods for estimating follow-up rates in cohort studies[END_REF]. We compared the sociodemographic characteristics between the sample of participants at baseline and the sample of participants who provided follow-up data (follow-up sample).

We assigned the reported highest education level according to the percentiles of "educational attainment by age": low (< 50th percentile) or high (≥ 50th percentile). We considered that "low educational attainment" corresponded to bachelor's degree or lower levels among participants aged 20-54 years, and to primary, general education or lower levels among participants of other ages. We divided household incomes into classes based on the French population in the 2015 census: low (≤ 30th percentile), medium (30th -80th percentile) and high (≥ 80th percentile) income.

We defined injury severity levels based on the type of medical care for the reported injuries in three mutually exclusive categories: 1) Hospitalization, 2) ED attendance, 3) Neither ED nor hospitalization. The last category includes medical care, nursing care, dental care, physiotherapy, other medical care, the care provided by the victim him/herself and non-medical personnel. In addition to this, we defined a secondary outcome, the injuries requiring any medical care, including hospitalization, ED attendance, and others care services. In addition, we grouped HLIs by place and activity, looking for similar circumstances of occurrence.

We calculated Crude Incidence Rates (CIR) and Standardized Incidence Rates (SIR) on the entire cohort for socio-demographic variables and groups of injury circumstances, mechanisms and severity levels. SIRs were calculated using direct standardization on the age and sex distribution in France in 2015. CIR and SIR 95% confidence intervals were computed using the Poisson approximation [START_REF] Fay | Confidence intervals for directly standardized rates: a method based on the gamma distribution[END_REF]. In addition, we described the typology of injury, injury body location, limitations on doing usual activities in the 48 h following the event, and the number of work and study days lost.

Results

Participants

Between November 2014 and December 2019, 12,419 people signed a consent form to participate in the MAVIE cohort and responded to the baseline questionnaires, and 8640 provided follow-up data at least once (Fig. 1). The median and maximum follow-up time were 4.0 years (Q 1 = 3.6, Q 3 = 4.5) and 5.2 years, respectively. The observed person-time was 6302 persons followed for 5.2 years. The person-time assuming no dropouts was 7312 persons followed for 5.2 years when considering the whole period from recruitment to the cut-off date (31 of December 2019). Loss to follow-up, defined as one less the ratio of those estimations (1-PTFR), was 13.8%.

Among the participants in the follow-up sample, 4511 were women (52%), and 4129 were men (48%). Their mean age was 50 ± 20 years, 48 ± 20 years for women, and 52 ± 20 years for men. The maximum age was 101 years. We observed differences between the baseline and follow-up samples concerning all variables except sex (Table 1). However, these differences were not relevant comparing figures of both samples. Additional file 1 shows the percentage of practitioners of different activities (domestic, gardening, DIY, sports, outdoor and indoor play) by age and sex.

HLIs frequency and incidence rates

Participants who provided follow-up data reported 3024 events between the inclusion and the cut-off date. Among them, 83 events did not match the HLIs criteria. We excluded 264 events because they occurred before or on the inclusion date. We excluded another 194 events because data related to the type of medical care, mechanism, place, or activity were not available. The analyses included 2483 HLIs (Fig. 1). Among participants, 6942 (80%) reported no injury, while 1698 (20%) reported at least one HLI during the period. 48% reported an event among the victims, the mean number of events was 1.5 ± 1.0, and the first event was 20 ± 15 months.

With 32,770 person-years of follow-up in the MAVIE cohort, we estimated the SIR of non-fatal HLIs (with or without medical care) in the French population at 85.0 HLIs per 1000 person-years (95% CI, 60.6-109.4). The CIR of HLIs was significantly higher in women, except in the 55-69 age group. We obtained a U-shaped curve, higher CIRs in children and in participants over 70 years of age. However, the CIR of HLIs was much higher among women over 70 years of age than among men of the same age (Fig. 2). The SIRs of HLIs were higher among members of high-income households; among higher managers, participants with professional occupations or independents and among retired or pre-retired people; among those living alone and in four-member households (Table 2).

Injury severity, mechanisms and circumstance of occurrence and consequences

Two out of three HLIs reported in the cohort had no severe consequences, and only 4% required hospitalization (Table 3). Despite this overall low level of severity, 73% of the HLIs were reported to be limiting or very limiting for everyday activities in the 48 h following the event (Additional file 2). However, 78% of the HLIs did not result in any work or study stoppage. Among the 14% who lost one or more work/school days, the mean was 22 lost days (Q 1 = 4 -Q 3 = 30). The total number of lost work/ study days was 613 per 1000 person-years; 38.3% of lost days were due to injuries that did not require ED attendance or hospitalization. We found that most HLI events resulted in single wounds (64%). The most affected body parts were the lower extremities (affected in 52% of the HLIs), the upper extremities (44%), and the head (22%). Contusions (with and without bruising) were the most common typology of injury (32%), followed by abrasion (13%) and sprains (13%). Fractures were the most common typology of injury among hospitalizations. Simple fractures accounted for 35% of hospitalizations, and open fractures for 28% (Additional file 3).

Struck or hit by falls was the mechanism with the highest SIR, followed by struck or hit by contact with objects, persons, or animals (Table 3). Struck or hit by falls was the mechanism that generated the highest number of hospitalizations (73% of HLIs ending with hospitalization). Crushing, cutting or piercing, and overexertion also had high SIR but the severity was generally lower (Additional file 4).

The home (50%), the public space (22%), and natural areas (12%) were the most frequent places where HLIs occurred. Walking (20%), sports activities (19%), domestic activities (14%), leisure activities (9%), DIY (9%), and gardening (7%) were the most frequent activities during which HLI occurred (Additional file 5). Table 3 shows the SIRs for each circumstance of occurrence, grouping the most common places and activities of reported HLIs. Among the circumstances, sports (without contact with nature) top the list, followed by play and leisure. Sports-related injuries affected mainly males, except among children and participants over 70 years old (Fig. 3). Sports, together with playing and leisure, were the circumstances that affected children and young adults the most. Sport, leisure, and playing circumstances frequently involved ED attendance and hospitalizations (36%), mainly among young adults. The highest proportion of HLIs leading to hospitalizations was found among HLIs during outdoor sports activities involving contact with nature (18%). Adults between 55 and 69 years of age were the most affected (67% of hospitalizations by HLIs in sport involving contact with nature). Outdoor sports HLIs occurred mainly while walking or running in HLIs that occurred while moving represented the second most frequent circumstance (26%), with 12% in public spaces (sidewalks, urban road areas), 6% while walking in the house, 5% while climbing stairs at home, and 3% in other circumstances related to mobility such as riding a bicycle or a scooter. These events primarily affected older adults, most frequently women (Fig. 3). HLIs leading to hospitalizations while moving around (at home or in public places) only concerned participants over 58 years of age.

HLIs were also frequent in the domestic sphere (26%), including do-it-yourself (DIY) activities (9%), gardening (7%), cooking (6%), and house cleaning (4%) (Table 3). DIY activities and gardening showed high SIRs mainly in men, DIY activities primarily in the over-35 age group (with a peak in the 55-69 age group) and gardening in the over-55 age group (Fig. 3). Hospitalizations related to DIY activities, and gardening activities predominantly affected participants around 50 years old. Women were slightly more affected by injuries while cooking or cleaning the house (Fig. 3). These activities presented the lowest frequency of ED attendance or hospitalization (5%).

Other relevant circumstances of HLIs were vital activities (including eating, sleeping, and daily personal hygiene). Both sexes and all ages were affected, but hospitalizations and ED attendances mainly concerned women of 70 years or more (Fig. 3).

Discussion

The follow-up of participants of the MAVIE cohort led us to estimate an annual SIR of 85.0 HLIs per 1000 person-years (95% CI, 60.6-109.4), measured for 5.2 years (period 2014-2019) and 6302 person-years of follow-up. More than half of HLIs did not require ED attendance or hospitalization. The annual sexstandardized SIR of HLIs was higher in those aged less than 15 and 70 or more. The annual age-standardized SIR of HLIs was higher among women. The CIR of HLIs was higher among women aged 70 or more. The annual SIR of HLIs was higher among participants of high-income households; among higher managers, participants with professional occupations or independents, and among retired or pre-retired people; among those living alone and in four-member households. The most common HLI mechanism was the fall (52% of all HLIs, 73% of HLIs ending with hospitalization), while the circumstance of occurrence of HLI that accounted for the highest SIRs of HLIs was sports without contact with nature. The most common circumstance of HLIs leading to hospitalization was outdoor sport activities (in contact with nature) (18%). Conversely, house cleaning and cooking rarely required ED attendance or hospitalization (5%). The estimated incidences in the MAVIE observatory were lower than those measured in other French studies. The annual SIR of HLIs requiring medical care was 39.7 per 1000 person-years, compared with 178 per 1000 person-years estimated by the ESPS in 2012 [START_REF] Paget | Les accidents de la vie courante en France Métropolitaine selon l'enquete santé et protection sociale 2012[END_REF]. The annual SIR of HLIs that required ED attendance or hospitalization was 290 per 1000 personyears, compared with 500 per 1000 person-years estimated by the ESPS in 2012 [START_REF] Paget | Les accidents de la vie courante en France Métropolitaine selon l'enquete santé et protection sociale 2012[END_REF]. The SIR of HLIs that required ED attendance or hospitalization among adults was 21.5 per 1000 personyears, compared with 48.7 per 1000 person-years in the EPAC survey (in the period between 2004 and 2008). A possible explanation for these differences is the underreporting of HLIs and severe HLIs in our sample. Further comparisons with other previous studies are problematic due to differences in designs, outcome definitions and data sources. Some population studies considered only adults [START_REF] Bonaldi | Estimates of home and leisure injuries treated in emergency departments in the adult population living in metropolitan France: a model-assisted approach[END_REF] or mainly men [START_REF] Verrier | Home and leisure injuries among the French electricity and gas company active employees: circumstances and short-term consequences[END_REF]. The HLI definition also varies, including sports injuries [START_REF] Bonaldi | Estimates of home and leisure injuries treated in emergency departments in the adult population living in metropolitan France: a model-assisted approach[END_REF] or not [START_REF] Verrier | Home and leisure injuries among the French electricity and gas company active employees: circumstances and short-term consequences[END_REF]. Finally, the data sources differ, with mortality data [START_REF] Lasbeur | Mortalité par accident de la vie courante en France métropolitaine 2000-2010 : focus sur les incendies[END_REF], data obtained from ED attendances [START_REF] Bonaldi | Estimates of home and leisure injuries treated in emergency departments in the adult population living in metropolitan France: a model-assisted approach[END_REF], the combination of ED attendances and medical consultation [START_REF] Richard | Les accidents en France : évolution et facteurs associés Injuries in France: Trends and risk factors[END_REF], or the combination of ED attendances and outpatient consultation [START_REF] Paget | Les accidents de la vie courante en France Métropolitaine selon l'enquete santé et protection sociale 2012[END_REF].

We included HLIs that did not require ED attendance or hospitalization because we considered them to be also relevant. Several studies have shown that injuries of any severity can deteriorate the quality of life and reduce Fig. 3 HLI crude incidence rate of HLI circumstances and age-sex groups: crude incidence rate per 1000 person-years, confidence intervals 95%. Events with no data on activity, place, or type of medical care were not included productivity [START_REF] Mcclure | Appropriate indicators for injury control?[END_REF][START_REF] Mulder | Setting priorities in injury prevention: the application of an incidence based cost model[END_REF]. We found that low-severity HLIs resulted in considerable loss of work or school days. We estimated 109.0 (36.1-301.8) days of work or school lost per 1000 person-years, or about 13.4 million days lost each year in France, in comparison with the 45.9 million days lost in 2019 due to reported work-related injuries (Rapport Annuel 2019, 2019).

In agreement with the literature [START_REF] Bonaldi | Estimates of home and leisure injuries treated in emergency departments in the adult population living in metropolitan France: a model-assisted approach[END_REF], the sex-standardized SIRs of HLIs were higher in children and adolescents and in persons aged 70 years and older. In contrast with the results of other French studies in the general population [START_REF] Paget | Les accidents de la vie courante en France Métropolitaine selon l'enquete santé et protection sociale 2012[END_REF][START_REF] Richard | Les accidents en France : évolution et facteurs associés Injuries in France: Trends and risk factors[END_REF], the age-standardized SIR was higher in women. The largest difference between men and women was found in participants aged 70 years and older, as described for falls [START_REF] Ek | Risk factors for injurious falls in older adults: the role of sex and length of followup[END_REF]. This difference may be due to the inclusion in our study of lowseverity HLIs, often related to domestic activities and recurrent low-severity falls. However, we cannot exclude underreporting of events among men, especially among those aged 70 years and older.

In contrast to other studies that showed that socially disadvantaged people have a higher risk of severe injuries and injuries requiring hospitalization [START_REF] Ferrante | Epidemiological risk analysis of home injuries in Italy (1999-2006)[END_REF][START_REF] Cubbin | Socioeconomic inequalities in injury: critical issues in design and analysis[END_REF], our study showed higher HLI SIRs among household members with higher incomes. This may be related to the grouping of home injuries with sports and leisure injuries in French studies, including ours. The higher participation in sports and leisure activities by members of high-income households may be part of the explanation. In contrast with previous French studies [START_REF] Paget | Les accidents de la vie courante en France Métropolitaine selon l'enquete santé et protection sociale 2012[END_REF][START_REF] Thélot | La surveillance épidémiologique des chutes chez les personnes âgées[END_REF][START_REF] Dalichampt | Les accidents de la vie courante selon l'Enquete decennale Sante 2002-2003[END_REF], we did not find high incidence rates among people with high educational levels, which may be due to the redefinition of the level of education depending on age. The SIRs of HLIs were higher among higher managers, participants with professional occupations, or independents. Greater exposure to sports and leisure activities and less experience doing DIY activities may also explain it. The higher SIRs rate of HLIs in retired or pre-retired people is probably related to the higher incidence rates of falls in older people [START_REF] Peeters | A comprehensive assessment of risk factors for falls in middle-aged adults: co-ordinated analyses of cohort studies in four countries[END_REF] and the exposition to certain risky activities as DIY and gardening. Similar reasons may also explain the higher SIRs rate of HLIs in people living alone, many of whom are older Fig. 4 Age of people by severity and activity/location groups. The black dots represent the average age. Abbreviation: ED: emergency department. Events with no data on activity, location or type of medical care were not included people. Increased SIRs for people living in 4-member households may be related to the presence of children at home, as shown by a recent study of home injuries in the United States [START_REF] Gielen | National survey of home injuries during the time of COVID-19: who is at risk?[END_REF].

As already suggested by other studies [START_REF] Verrier | Home and leisure injuries among the French electricity and gas company active employees: circumstances and short-term consequences[END_REF][START_REF] Epac | Enquête Permanente sur les accidents de la vie courante[END_REF]INVS, 2017), our study shows that incidence, causes, and consequences of HLIs differ by age group and sex, and are related to the performance of different activities. During the study of the circumstances of occurrence of HLIs, patterns of occurrence have emerged: playing games and playing sports in children; playing sports among adolescents, young adults and particularly among men; household activities (cooking, cleaning, etc.) among middle-aged adults and older adults, especially women; DIY and gardening among men, middle-aged adults and older adults, especially older men; mobility (in the public space, at home, going up and downstairs) in women, especially older women; and life activities in older adults.

A high incidence rate of sport-related HLIs in the MAVIE cohort was expected, as the practice of sports in France is frequent, especially outdoor sports. According to a survey on sports practices conducted in 2018 by the Ministry of Sports (INSEP, 2010), two-thirds of French people aged 15 years and older reported doing physical activity at least once a year, and only 18% reported never having practiced sports or physical activity. Among the French adults, 85% of men and 76% of women between 15 and 74 years of age reported practicing sports other than leisure and utility walking. The percentages were 46% for men and 34% for women aged 75 and over (INSEP, 2010).

In our study, we identified nature as a place where severe HLIs occurred frequently. HLIs leading to hospitalization occurred most frequently during the practice of outdoor sports activities (in contact with nature) (18%).

Another finding of our study was the higher proportion of severe HLIs in persons aged 50 to 70 years (48% of all severe HLIs that required hospitalization). Sports, including outdoor sports, gardening, and housework, were frequent circumstances of the most severe HLIs. Hospitalizations for mobility-related HLIs (at home or in public places) only affected persons older than 58. This result is consistent with the known importance of falls in the elderly.

Strengths and limitations

The main strengths of the MAVIE observatory are associated with the web-based management and the prospective design of the cohort [START_REF] Rojas-Castro | Cohort profile: MAVIE a web-based prospective cohort study of home, leisure, and sports injuries in France[END_REF]. Web-based management simplified logistics (invitations, registration, data collection, and follow-up), reduced recruitment costs and facilitated the implementation of different strategies to attract the attention or retention of participants. The prospective design contributed to reducing recall bias and ensured that the exposures preceded the HLI events [START_REF] Rojas-Castro | Cohort profile: MAVIE a web-based prospective cohort study of home, leisure, and sports injuries in France[END_REF].

Our study had limitations common to other volunteer-based cohorts and e-cohorts. The response rate was low; the analyses included 8638 people, while almost 4 million e-mail invitations had been sent. The follow-up rate (86.3%) was higher than the 60-80% range considered acceptable by some authors [START_REF] Kristman | Loss to follow-up in cohort studies: how much is too much?[END_REF]. The MAVIE cohort differs demographically from the French population: children, adolescents, young adults, and participants aged 75 years or older are underrepresented. Participants between 50 and 70 years of age, and participants of high socioeconomic and educational level are overrepresented. Previous research summarizes our efforts to deal with representativeness, loss of follow-up, and information quality [START_REF] Rojas-Castro | Cohort profile: MAVIE a web-based prospective cohort study of home, leisure, and sports injuries in France[END_REF].

The underrepresentation of young people may have led to underestimating the incidences of sports and leisure time injuries. The underrepresentation of persons older than 75 years may have led to an underestimation of the incidences of falls while moving. The possible overrepresentation of participants with a history of HLIs (because a recent HLI in the family or friends circle would have motivated them to participate) may have led to an overestimation of the incidence of HLIs. We discarded events that occurred just at entry into the cohort (264 events in total) to reduce this possible bias.

The lack of representativeness implies that incidence estimates should not be generalized and should be used exclusively to compare subgroups and study risk factors [START_REF] Richiardi | Commentary: Representativeness is usually not necessary and often should be[END_REF]. The generalization of these results to the French population should be made with caution. Methods such as calibration, stratification and imputation could help correct the lack of representativeness [START_REF] Keiding | Web-based enrollment and other types of self-selection in surveys and studies: consequences for generalizability[END_REF] in future studies. The following steps of the research are the study of risk factors for HLIs, for which the sample is not required to be representative of the general population [START_REF] Keiding | Web-based enrollment and other types of self-selection in surveys and studies: consequences for generalizability[END_REF]. We intend to study the intrinsic and environmental risk factors for each type of HLIs, when the sample size and number of events allow it.

Conclusion

Despite the limitations, the present study provides a broad picture of the public health burden of the main types of HLI in the French population, particularly those of minor and moderate severity. We show that HLIs differ qualitatively and quantitatively by age group. Emerging patterns of occurrence are mainly related to sports and leisure, mobility, DIY work, domestic and gardening activities. Considering that these patterns are the product of the risk of a given activity, the time spent on the activity (exposure time), and possible individual vulnerabilities, further analyses should focus on disentangling these factors. Our results support the utility of prevention interventions, policies, and campaigns targeting sub-populations and specific types of HLIs. Understanding which modifiable factors can reduce risk by age group and specific activities is essential for the success of these programs.

Fig. 1

 1 Fig. 1 Flow diagram for the selection of the individuals and the HLI events

Fig. 2

 2 Fig. 2 HLI crude incidence rate by age-sex group: crude incidence rate per 1000 person-years, 95% confidence intervals

Figure 3

 3 Figure3shows the CIRs for each circumstance of occurrence by age and sex group, and Fig.4shows the age distribution of injured participants by HLI severity and circumstances.Among the circumstances, sports (without contact with nature) top the list, followed by play and leisure. Sports-related injuries affected mainly males, except among children and participants over 70 years old (Fig.3). Sports, together with playing and leisure, were the circumstances that affected children and

Table 1

 1 Comparison of the MAVIE baseline and follow-up samples

	Participants Characteristics	Baseline Sample		Follow-up Sample		P-value
	All	n = 12,419	(%)	n = 8640	(%)
	Sex
	Male	5838	(47)	4129	(48)	0.270
	Female	6581	(53)	4511	(52)
	Age groups (years)
	< 15	999	(8)	763	(9)	< 0.001
	15-34	1795	(14)	1092	(13)
	35-54	3584	(29)	2297	(27)
	55-69	4539	(36)	3396	(39)
	≥ 70	1502	(12)	1092	(13)
	Occupational Status (≥ 15 years old)
	Farmer, operators, craftsman, shopkeeper	127	(1)	91	(1)	< 0.001
	Higher manager, professional occupations, independent	1783	(17)	1347	(19)
	Middle manager, employees	2386	(25)	1619	(19)
	Retired	3819	(41)	3017	(43)
	Unemployed	871	(9)	615	(8)
	Student	299	(3)	192	(2)
	Other	312	(3)	202	(3)
	missing	1823		794
	Educational attainment by age (≥ 15 years old)
	Low	8738	(91)	6515	(92)	0.038
	High	868	(9)	575	(8)
	missing	1819		787
	Household Characteristics
	All	9483		6356
	Number of household members
	1 member	2198	(23)	1563	(25)	< 0.001
	2 members	4211	(44)	2953	(46)
	3 members	1308	(14)	788	(12)
	4 members	1222	(13)	756	(12)
	5 members	408	(4)	228	(4)
	6 members and more	113	(1)	53	(1)
	missing	23		15
	Household income level
	Low ≤ p30	1177	(14)	704	(13)	0.006
	Medium (p30 -p80)	3319	(41)	2258	(41)
	High ≥ p80	3651	(45)	2598	(47)
	missing	1336		796

Table 2

 2 Number of victims, events and the HLIs incidence rates in relation to demographic variables in the MAVIE follow-up sample

	Participants Characteristics	Injured a (%)	HLIs b CIR (95% CI) c		SIR (95% CI) d
	All	1698	(20) 2483	75.8	(72.8 -78.8)	85.0	(60.6 -109.4)
	Sex
	Male	806	(19)	1158	72.3	(68.2	-76.6)	75.0	(51.3	-98.7)
	Female	892	(20)	1325	79.0	(74.8	-83.4)	94.4	(69.3	-119.5)
	Age groups (years)
	15	184	(24)	285	107.7 (95.5	-120.9) 109.1 (78.2	-140.1)
	15-34	189	(17)	293	75.6	(67.2	-84.8)	76.4	(48.2	-104.7)
	35-54	411	(18)	584	66.6	(61.3	-72.2)	65.5	(50.1	-80.9)
	55-69	687	(20)	994	73.9	(69.4	-78.6)	72.7	(61.2	-84.1)
	≥ 70	227	(21)	327	81.2	(72.7	-90.6)	123.7 (79.2	-168.3)
	Occupational Status (≥ 15 years old)
	Farmer, operators, craftsman, shopkeeper	13	(14)	17	47.2	(27.5	-75.6)	-	-	-
	Higher manager, professional occupations or independent 293	(22)	422	80.3	(72.8	-88.3)	-	-	-
	Middle manager, employee	276	(17)	401	64.0	(57.9	-70.5)	-	-	-
	Retired	671	(22)	984	81.8	(76.8	-87.1)	-	-	-
	Unemployed	110	(18)	168	69.7	(59.5	-81.0)	-	-	-
	Student	32	(17)	48	71.6	(52.8	-94.9)	-	-	-
	Other	39	(19)	59	76.1	(57.9	-98.2)	-	-	-
	Educational attainment by age (≥ 15 years old)
	Low	91	(16)	123	(55)	(46.8	-67.2)	-	-	-
	High	1345	(21)	1978	(77)	(73.9	-80.7)	-	-	-
	Member in a household of
	1 member	367	(23)	587	97.0	(89.3	-105.1) -	-	-
	2 members	770	(19)	1090	71.3	(67.2	-75.7)	-	-	-
	3 members	195	(16)	266	57.5	(50.8	-64.9)	-	-	-
	4 members	270	(21)	403	84.2	(76.2	-92.8)	-	-	-
	5 members	72	(17)	106	68.8	(56.3	-83.2)	-	-	-
	6 members and more	19	(18)	25	61.6	(39.9	-90.9)	-	-	-
	Member in a household with an income level
	Low ≤ p30	133	(19)	183	57.5	(49.5	-66.5)	-	-	-
	Medium (p30 -p80)	543	(24)	77	69.9	(65.1	-74.9)	-	-	-
	High ≥p80	848	(33)	1237	84.9	(80.3	-89.8)	-	-	-

a Number of people who declared being affected by at least one injury b Number of HLIs adding up all HLIs per person c Incidence rate per 1000 person-years d Standardized incidence rate by the France age-sex distribution demographic population estimates in 2015 per 1000 person-years Abbreviations: HLIs Home Leisure Injuries, CIR Crude Incidence Rate, SIR Standardized Incidence Rate, CI Confidence Interval environments such as mountains and forests (Additional file 6).

Table 3

 3 HLI incidence by type of medical care, mechanism and circumstance of the injury event (activity and location) Variable with several possible answers, the percentages of the column do not add up to 100 % of the total number of injuries reported. Events with no data on the type of medical care, mechanism or circumstance, activity or location were not included Abbreviations: HLIs Home Leisure Injuries, CIR Crude Incidence Rate, SIR Standardized Incidence Rate, CI Confidence Interval

	HLIs Characteristics	HLIs a (%)		CIR b (95% CI)		SIR c (95% CI)
	Type of medical care d (n = 2344)
	No ED attendance or hospitalization	1602	(64)	48.9	(46.5	-51.3)	53.2	(51.1	-55.3)
	ED attendance	631	(25)	19.3	(17.8	-20.8)	22.8	(21.9	-23.7)
	Hospitalization	111	(4)	3.4	(2.8	-4.1)	3.9	(3.7	-4.0)
	Mechanism d (n = 2404)
	Struck/hit by fall	1241	(52)	37.9	(35.8	-40.0)	35.6	(34.2	-37.0)
	Struck/hit by contact with object, person, animal	566	(23)	17.3	(15.9	-18.8)	18.6	(17.9	-19.3)
	Crushing, cutting, piercing	420	(17)	12.8	(11.6	-14.1)	11.8	(11.3	-12.2)
	Acute overexertion of body or body part	330	(14)	10.1	(9.0	-11.2)	9.0	(8.6	-9.3)
	Thermal effect	100	(4)	3.1	(2.5	-3.7)	3.1	(3.0	-3.3)
	Chemical effect	24	(1)	0.7	(0.5	-1.1)	1.1	(1.0	-1.1)
	Other	19	(< 1)	0.6	(0.3	-0.9)	1.6	(1.5	-1.6)
	Circumstance (n = 2440)
	Sport (without contact with nature)	319	(13)	9.7	(8.7	-10.9)	15.2	(14.6	-15.8)
	Play and leisure	229	(9)	7.0	(6.1	-8.0)	11.2	(10.7	-11.6)
	Mobility in public spaces	291	(12)	8.9	(7.9	-10.0)	8.3	(8.0	-8.6)
	Sport outdoors in contact with nature	230	(9)	9.7	(6.1	-8.0)	5.9	(5.7	-6.1)
	Vital activities	130	(5)	4.0	(3.3	-4.7)	5.6	(5.4	-5.9)
	Cooking	152	(6)	4.6	(3.9	-5.4)	5.0	(4.8	-5.2)
	Walking in the house	151	(6)	4.6	(3.9	-5.4)	5.2	(5.0	-5.4)
	DIY	216	(9)	6.6	(5.7	-7.5)	4.7	(4.5	-4.9)
	Climbing stairs in the house	121	(5)	3.7	(3.1	-4.4)	4.4	(4.2	-4.6)
	Gardening	165	(7)	5.0	(4.3	-5.9)	3.5	(3.3	-3.6)
	Other domestic activity	104	(4)	3.2	(2.6	-3.8)	2.8	(2.7	-2.9)
	House cleaning	100	(4)	3.1	(2.5	-3.7)	2.7	(2.6	-2.8)
	Other mobility	73	(3)	2.2	(1.7	-2.8)	2.4	(2.3	-2.5)
	Other	126	(5)	3.8	(3.2	-4.6)	4.5	(4.4	-4.7)

a Number of HLIs adding up all HLIs per person b Incidence rate per 1000 person-years c Standardized incidence rate by the France age-sex distribution demographic population estimates in 2015 per 1000 person-years d

Acknowledgments

The authors express their thanks to all IETO team members for their help especially Léa Bled, Mélanie Nee, Guillaume Valdenaire, François Masson, Cédric Gil-Jardiné, Juan Naredo Turrado, Li Lu and Marie-Odile Coste.

Supplementary Information

The online version contains supplementary material available at https://doi. org/10.1186/s40621-021-00343-9.

Availability of data and materials

Personal health data underlying the study are protected by the French Data Protection Act and cannot be shared publicly. The large number of variables allows data to be indirectly identifiable and making such data freely available is prohibited. Furthermore, an authorization from the Commission Nationale de l'Informatique et des Libertés, the French Data Protection Authority, may be required to transfer the data, especially abroad. The MAVIE observatory protocol was approved by the Commission Nationale de l'Informatique et des Libertés on May 28, 2013(decision DR-2013-288). Data from this study can be obtained upon request from the steering committee (http://www. observatoire-mavie.com/contacter-equipe-MAVIE.aspx), as well as from the corresponding author (emmanuel.lagarde@u-bordeaux.fr).

Declarations

Ethics approval and consent to participate

The French Data Protection Authority approved the protocol of this study. The study is declared to the CNIL under file number 912292. Identifying data were stored on servers located in a different location from those hosting the main database. Electronic informed consent was collected from all adult participants. Participation of children was done under the responsibility and with the consent of a legal guardian.

Consent for publication

Not applicable.

Competing interests

The authors have declared that no competing interests exist.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Keywords: Power Electronics, integrated magnetic components, high frequency power losses, air gap effects

Analytical expressions based on the one dimensional field solution derived to compute windings losses in high frequency transformers could also be applied, under certain assumptions, to estimate losses in integrated magnetic components. To validate this approach, AC losses of two types of integrated components were analytically and numerically estimated, and the results are verified by the experimental measurement.

I. INTRODUCTION

High frequency winding losses in transformers are generally estimated using the one dimensional field solution addressed in [START_REF] Dowell | Effects of Eddy Currents in Transformer Windings[END_REF], [START_REF] Ferreira | Improved Analytical Modeling of Conductive Losses in Magnetic Component[END_REF]. Moreover, the orthogonality recognized by Ferreira allows the two terms of the high frequency losses, skin effect and proximity effect, to be analytically separated. For components with air gapped cores, many techniques [START_REF] Kirchenberger | A Contribution to the Design Optimization of Resonant Inductors for High Power Resonant DC-DC Converters[END_REF], [START_REF] Meinhardt | New Method for Integration of Resonant Inductor and Transformer-Design, Realization, Measurements[END_REF] and [START_REF] Hu | AC Resistance of Planar Power Inductors and the Quasidistributed Gap Technique[END_REF], are proposed to minimize the air gap effects and to maintain the one dimensional field solution.

Integrated magnetic components which contain capacitive and inductive components present advantages in minimizing the cost and volumes. For designers, this integration introduces some difficulties in recognizing the magnetic field distribution in the window area, and accordingly for winding losses estimation. In this situation, numerical solutions such as the finite elements programs are usually preferred to calculate the losses and to visualize magnetic field distributions. However, numerical methods are not compatible with optimization lines and become limited and expensive in time and memories for a standard PC. This paper explores the application of the one dimensional field solution to estimate analytically winding losses in an integrated magnetic component, shown in Fig. 2, under the following assumptions:

1) Air gap effect can be neglected using the techniques proposed in [START_REF] Kirchenberger | A Contribution to the Design Optimization of Resonant Inductors for High Power Resonant DC-DC Converters[END_REF], [START_REF] Meinhardt | New Method for Integration of Resonant Inductor and Transformer-Design, Realization, Measurements[END_REF] and [START_REF] Hu | AC Resistance of Planar Power Inductors and the Quasidistributed Gap Technique[END_REF], where fringing flux can still be very close to the air gap zone. Hence, the presence of a onedimensional magnetic field in the rest of the window area becomes obvious.

2) The presence of a one-dimensional magnetic field allows the primary and secondary winding losses to be estimated using Dowell [START_REF] Dowell | Effects of Eddy Currents in Transformer Windings[END_REF] or Ferreira [START_REF] Ferreira | Improved Analytical Modeling of Conductive Losses in Magnetic Component[END_REF] methods.

3) For the center leg windings, only DC losses will be considered because of the reduced output current ripple, and the influence of the air gap negligible.

To verify this approach, two types of integrated magnetic components are designed and implemented. Windings losses are analytically estimated and compared with the results obtained by a finite elements tool. The AC resistance of the windings is measured too.

II. SELECTED INTEGRATED MAGNETIC STRUCTURES

Magnetic components used in the DC-DC converter shown in Fig. 1 (a) could be integrated [START_REF] Yan | Integrated Magnetic Full Wave Converter with Flexible Output Inductor[END_REF], [START_REF] Sun | Integrated Magnetics for Current-Doubler Rectifiers[END_REF] into one single magnetic core, Fig. 1 (b). The output filtering inductance presented by the integrated structure is given as:

O C S C O R R N N L 5 . 0

A. Planar integrated magnetic component 1) Analytical approach

An integrated magnetic component, shown in Fig. 2, is designed and implemented, for 1kW, 48V, DC-DC converter, with an operating frequency of 150 kHz. Primary windings (20turns) are constructed using a foil of (7mm x 0,2mm) dimensions, secondary windings (7 turns) are constructed using a foil of (2//: 9 mm x 0,2mm), central windings (3 turns)with a foil of (2//: 4mm x 0,3mm). Transformer windings losses can be estimated in the m th layer as follows:

2 2 1 ] ) 1 2 ).( cos cosh sin sinh ( ) cos cosh sin sinh [( 2 rms h h h h h n h h h h h h dc t I m R P - + - + - + = ∑ = γ γ γ γ γ γ γ γ γ (2)
Where:

h δ λ γ / =
λ is the thickness of the foil and δ h is the skin depth of the corresponding harmonic.

As already indicated, for the central leg winding, only conduction losses are taken into account because of the reduced output current ripple and when one of the techniques proposed in [START_REF] Kirchenberger | A Contribution to the Design Optimization of Resonant Inductors for High Power Resonant DC-DC Converters[END_REF], [START_REF] Meinhardt | New Method for Integration of Resonant Inductor and Transformer-Design, Realization, Measurements[END_REF] and [START_REF] Hu | AC Resistance of Planar Power Inductors and the Quasidistributed Gap Technique[END_REF] is applied. Notice that no electromagnetic interaction is assumed in the window area between the central leg windings and the transformer windings

3) Results

Windings losses are estimated in the 2D plan and represented in the Table І. As can be seen in the table І, central leg winding losses keep the same value with a single or a distributed air gap. Then, losses due to the fringing air gap field could be satisfactory neglected even with a single air gap when the output current ripple is enough reduced. Consequently, this will be considered as another advantage of this integrated magnetic structure, introduces more simplification in designing and losses estimation. In the other hand, an error was introduced in calculating secondary windings losses, where each layer of secondary is formed using two foils in parallel. Moreover, analytical estimation doesn't take into account the magnetic field distribution for the outer windings which is not totally a one-dimensional.

B. Integrated magnetic component using Litz wire

An integrated structure shown in Fig. 6 was built using Litz wires and a magnetic core type of (E55/28/21), with:

• Total primary turns In neglecting the twist of strands, the homogenization conception [START_REF] Matagne | Modélisation Magnétique Macroscopique des Faisceaux de Conducteurs)[END_REF], [START_REF] Nan | An Equivalent Complex Permeability Model for Litz-Wire Windings[END_REF] and [START_REF] Dedulle | Homogenization for non linear problems applied to the modelling of transformers[END_REF], allows a Litz wire exposed to an uniform transversal magnetic field ex H varying sinusoidal respect to time, to be dialed as a solid conductor with a complex permeability (

K µ µ µ µ µ µ µ µ µ µ ⋅         + - -         + - + = * 1 1 (4)
And:

S er J J J J µ γ γ γ γ µ ⋅         - + = ) ( 2 ) ( 0 ) ( 2 ) ( 0 (5) r j ⋅ ⋅ = δ γ 2 2 / 3 (6)

1) Analytical estimation of windings losses

Litz wires losses can be estimated using classical expressions [START_REF] Reatti | Solid and Litz Wire Winding Non-linear Resistance Comparaison[END_REF] and [START_REF] Ferreira | Analytical Computation of AC Resistance of Round and Rectangular Litz Wire Windings[END_REF], derived from the exact solution of losses in a round conductor placed in a perpendicular and one dimensional field. The magnetic field distribution, shown in figure.6, visualized using the FE tool in the window area when the structure works as a transformer, justifies the application of the one dimensional field solution. Then, Litz winding losses are given as:

2) Numerical Simulation of Litz windings

In the light of the homogenization conception, magnetic components with Litz wires can be numerically simulated using finite elements tools. Proximity losses are numerically estimated in replacing Litz wires by homogenized solid conductors with a correspondent complex permeability. On the other hand, skin losses could be separately estimated (9) using the orthogonality conception [START_REF] Ferreira | Improved Analytical Modeling of Conductive Losses in Magnetic Component[END_REF], and then be added to proximity losses.

3) Experimental measurements

The series resistance measured for primary and secondary windings is 43 mΩ measured at 150 kHz, and the DC resistance is 22.3 mΩ as shown in figure 7. For I rms = 6.7 A of primary current, Then, primary and secondary windings losses for the first seven harmonics are given as: Analytical formulas used to estimate winding loses in a classical transformer were extended to be applied for integrated magnetic components. The effects of magnetic fringing flux could be neglected in integrated components such as the studied structure when the output current ripple is enough reduced. Beside the analytical formulas applied to estimate litz wire windings, a method based on the homogenization was numerically and analytically applied, and experimentally verified.

  and R O are the reluctances of the center leg and the outer leg respectively. Analytical and Numerical Contributions for Winding Losses Estimation in an Integrated Magnetic Component Aiman KERIM, Jean-Paul FERRIEUX, James ROUDET, Gérard MEUNIER Grenoble Electrical Engineering Laboratory (G2Elab) ENSIEG -BP46 38402 St MARTIN D'HERES Cedex FRANCE (a) (b) Fig. 1: Studied structure with: (a) discrete magnetic components, (b) integrated magnetic component III. WINDING LOSSES ESTIMATION

Figure. 2 :Figure. 3 :

 23 Figure.2: Planar integrated magnetic component. So, for central windings losses we have: 2 _ o DC c c I R P = (3) Where DC c R _ is the dc resistance of the central leg windings, and o I is the output dc current.

  Figure.4: AC measured resistance of the transformer constructed using vertical foils and a planar core.

  of strands in the conductor. r : Radius of the strand in (m). R : Radius of the homogenized conductor in (m). δ : Skin depth in (m).

Sµ:

  Magnetic permeability of the strand material.

dµ: 5 :Figure. 6 :

 56 Magnetic permeability of the dielectric medium. Magnetic field distribution in the window area when the integrated structure works as: (a) a transformer, (b) an inductor. Principle of the Homogenization (a)Litz wire, (b) homogenized Litz wire.

  losses could be given per unit length for a homogenized Litz conductor as:

  in the transformer windings, primary and secondary, are the sum of proximity losses listed in TableII, and skin losses are calculated using[START_REF] Nan | An Equivalent Complex Permeability Model for Litz-Wire Windings[END_REF] as: d s = 0.1 mm (diameter of the strand) difference between P mesured and P can be explained, on the one hand, by the 2D modeling used for simulation and, on the other hand by the error due to the low resistance measurement.

Figure 7 :

 7 Figure 7: AC measured resistance of the transformer IV. CONCLUSION


Arthur Desbois

Tiziana Cattai

Marie-Constance Corsi

Fabrizio De

Vico Fallani

Fabrizio

Functional Connectivity for BCI: OpenViBE implementation

A possible way of interpreting electroencephalography (EEG) data is in terms of functional connectivity between channels, describing how brain areas mutually interact. Brain connectivity can be modeled as graphs, and mental states have been shown to be characterized by particular graph statistics (e.g. node strength or node efficiency) [START_REF] Gonzalez-Astudillo | Networkbased brain computer interfaces: principles and applications[END_REF]. Linking connectivity features to mental states can be a path to enhancing BCI performance.

OpenViBE is an open-source C++ based framework allowing real-time acquisition and processing of EEG data in a modular way, but algorithms and solutions for measuring and post-processing connectivity information are missing.

Based on previous works (3) , we implemented different connectivity algorithms in OpenViBE: magnitude squared coherence and imaginary part of coherence [START_REF]Identifying true brain interaction from EEG data using the imaginary part of coherency[END_REF]. We ensure low complexity by using the Eigen library (4) for algebraic operations, and implementing Welch's method (5) for computing the periodograms. We also developed matrix manipulation methods for post processing, and Graph Laplacian « denoising » (3).

We show this implementation is feasible for real-time Motor Imagery experimental protocols, as computing a single connectivity measure across 2 seconds of signal sampled at 512Hz, using 74 channels and 128 frequency bins takes less than 25ms on a typical workstation. When using 256 channels, this measure takes approximately 150ms, and 300ms when also using 256 frequency bins.

Research is currently ongoing to use functional connectivity as the basis for graph representation of the underlying brain networks, or with classification algorithms as an alternative feature to spectral power to discriminate between different Motor Imagery tasks: rest vs activity.

Functional

  Connectivity for BCI: OpenViBE implementation A. Desbois, T. Cattai, M.-C. Corsi, F. De Vico Fallani Inria, Aramis project-team, Paris Brain Institute -Institut du Cerveau (ICM), Inserm U 1127, CNRS UMR 7225, Sorbonne Université, F-75013, Paris, France