{
  "abstract": "Background Children with epilepsy are at increased risk of Sudden Unexpected Death (SUDEP). The pathophysiology of SUDEP remains unclear however ictal respiratory disturbances can be significant. The risk of SUDEP varies but is estimated to be 1.2/1,000 children with epilepsy per year. SUDEP most often occurs during sleep. PneumoWave is a small chest-worn accelerometer which measures changes in chest wall motion ( figure 1). Using a wearable sensor alerting carers to apnoeas could save lives.Aims (1) Determine the feasibility of collecting chest motion data from a novel, accelerometer-based sensor, PneumoWave (PneumoWave Ltd, UK) in children attending for video telemetry (VT) at the Royal Hospital for Children, Glasgow. (2) Improve understanding of chest motion changes in peri-ictal period.Methods An observational feasibility study over a 2-year period. Measurements include (1) chest wall motion measured by the worn biosensor, (2) standard monitoring VT and oximetry data, (3) Parents/ carers and patient feedback questionnaires to assess experience and tolerability. Cardiorespiratory changes 15 minutes before and after events will be mapped. Algorithms are in development to allow for automated evaluation of motion metrics.Results 18 VT patients [17 wearing the sensor] with a range of age (14 months to 16 years of age), weight (8.64kg to 94.6kg), epilepsy types and comorbidities were recruited. The sensor was well tolerated by all patients who wore it. 1,135 hours of biosensor has been collected and 19 epileptic seizures recorded with 3 post-ictal central apnoeas identified in addition to apnoeas during sleep and breath holding episodes ( figure 2).Conclusion This multidisciplinary study evaluates the feasibility of collecting chest motion data from children at risk of SUDEP using a novel biosensor. We examine the biosensor’s potential for real-time respiratory monitoring, providing insights into changes in respiratory pattern architecture during the peri-ictal period and supporting intervention strategies.Abstract O4 Figure 1PneumoWave data workflow. The PneumoWave sensor attaches to the patient’s chest using an ECG electrode. Accelerometery data is transferred via Bluetooth to a data capture mobile application (DCM). Data is processed in a cloud-based infrastructure and a combined waveform us generates (displayed on MATLAB for demonstration purposes). Algorithms are in development to identify respiratory metrics such as respiratory rate,pattern and central apnoeas. ECG, electrocardiogramAbstract O4 Figure 2(A) 15 years 7-month female, drug resistant focal epilepsy, DEPDC5 mutation, event at 02:36:25: A brief period, lasting 7 seconds of dystonic posturing of limbs is associated with lower amplitude background with fast/ muscle activity superimposed, muscle artefact is prominent particularly over the left hemisphere. (B) 15-years 7-month female, drug resistant focal epilepsy, DEPDC5 mutation, apnoeas during period of sleep. (C) 11-year 3-month female with Rett syndrome and epilepsy, VT to capture apnoeic events and time in relation to epileptic seizures. Eyes rolled back, then staring, stopped breathing, staring. Spike wave activity is seen on the EEG at the time of the event marker pressed (08:33:40), run of widespread delta activity. Green box, central apnoea: Red box oxygen desaturation ≥3%",
  "authors": [
    {
      "affiliations": [
        "Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom"
      ],
      "name": "Hannah Vennard"
    },
    {
      "affiliations": [
        "Paediatric Respiratory Medicine, Royal Hospital for Children, Glasgow, United Kingdom"
      ],
      "name": "Elise Buchan"
    },
    {
      "affiliations": [
        "PneumoWave Ltd, Glasgow, United Kingdom"
      ],
      "name": "Jennifer Miller"
    },
    {
      "affiliations": [
        "PneumoWave Ltd, Glasgow, United Kingdom"
      ],
      "name": "Stuart Kelly"
    },
    {
      "affiliations": [
        "PneumoWave Ltd, Glasgow, United Kingdom"
      ],
      "name": "Catriona Cowan"
    },
    {
      "affiliations": [
        "PneumoWave Ltd, Glasgow, United Kingdom"
      ],
      "name": "Osian Meredith"
    },
    {
      "affiliations": [
        "PneumoWave Ltd, Glasgow, United Kingdom"
      ],
      "name": "Bruce Henderson"
    },
    {
      "affiliations": [
        "Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom"
      ],
      "name": "David Lowe"
    },
    {
      "affiliations": [
        "Paediatric Neurology Department, Royal Hospital for Children, Glasgow, United Kingdom"
      ],
      "name": "Sameer Zuberi"
    },
    {
      "affiliations": [
        "Paediatric Respiratory Medicine, Royal Hospital for Children, Glasgow, United Kingdom"
      ],
      "name": "Ross Langley"
    }
  ],
  "title": "O4 A diagnostic feasibility study of a novel accelerometer-based chest sensor in children at risk of sudden death in epilepsy",
  "uid": "d3fee8c6-c7a6-595e-a90c-46f86ad2bb40"
}