IoT snoring sound detector prototype as a model of future participatory healthcare

1. Introduction

Where speech is primarily intended, snoring is an unintended sound production mechanism, resulting from the interaction of the respiratory airflow with the vocal pathway of a sleeping person. The produced sound originates from the flow induced vibrations of different relaxed obstructions in this pathway, functioning as acoustical sources [1], like the nasopharynx, the velum, the oropharyngeal area, the tongue base and the epiglottis as is known in the VOTE classification scheme [2]. As snoring is related to a degree of respiratory airflow obstruction, severe levels of obstruction can lead to an intermittent shortage in oxygen supply, a physiological dangerous condition, labeled as obstructive sleep apnoea (OSA). Patient monitoring techniques and related therapy support including a telemedicine approach have been applied in the treatment of such patients [3]. The recording and analysis of snoring sounds can be part of a sleep-tracking technology giving opportunities in assessment, e.g. of the upper airway anatomy during sleep [4]. Snoring sounds are important elements of the nocturnal sounds, which have been shown to provide a good estimation of sleep architecture and quality [5]. In a new snoring detection device the snoring event extraction was based on a new hysteresis algorithm [6]. In addition, machine learning is offering additional opportunities in specific use of snoring characteristics, as the snoring frequency has been shown to relate to sleep apnoea [7].

According to the technological evolution, connected portable devices with specialized functionality have become commodity products, giving a boost in collecting and storing medical data of patients. Due to their attractive characteristics e-health and m-health devices find their use in, amongst others, insonia management [8], cardiovascular medicine [9], screening of elderly cognitive impairment [10]. They can consist of standard devices (e.g. smart-phones, tablets) or can be implemented as wearable devices [11], realized as flexible hybrid electronics [12]. These products, acting as Internet of Things (IoT)-devices, are receiving acceptance from medical professionals and governments as additional modalities of practice in the healthcare ecosystem. The e-health ecosystem itself consists mainly of data providers (measurement devices), resource providers (operating the communication platforms for data exchange) and brokering parties levering secure services to manage private data and requests. In view of the healthcare ecosystem, participatory healthcare [13, 14, 15] is considered as an modus operandus for deploying healthcare where the patient is engaged and activated through participation in decision making. Considering the provision of data, in traditional healthcare a patient visits a hospital or specialized center in order to obtain the desired measurement results from highly functional specific medical equipment, as decided by the physician accordingly to clinical symptoms and signs. In this way, the hospital as owner of the medical devices is providing its traditional services. The recent COVID-19 pandemic has shown that the traditional modality of providing medical care has been disrupted with indications of a large number of patients with undiagnosed conditions [16] and with an important shift towards different types of telemedicine [17].

Where device ownership is common with wearables (e.g. smartwatches to follow heartrate, activity level and sleep stages [18]), it is limited in case of non-intrusive devices. In this study a low cost IoT snoring sound detector to be placed at a fixed place in the sleeping room was developed with the focus on such use at home. The system allows for patient controlled snoring sound recording and automated signal processing, resulting in patient specific reports of the personal sleep pattern.

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3. System performance

4. Discussion and conclusion

As demonstrated, the realized device can integrate data collection, data processing and data distribution in a single system. The use of a dedicated non-intrusive device is, in our view, preferred to guarantee identical conditions for the long term monitoring with minimal effort in operation and maintenance. It offers the flexibility to consistently select a single specific measurement position (below the bed, next to the bed, above the bed, or even integrated in the sleeping room) to guarantee the quality of follow-up measurements. This is in contrast to the use of a smartphone with a ‘snoring sound detection’ app, which could offer similar functionality [8]. The use can be tailored to the different user roles of the stakeholders by enabling the authorization levels for accessing the different functions. Where the patient (and his home mates) in combination with the medical specialist (and his assistants) are the main stakeholders, it could be expanded to additional professionals like home care givers. The flexibility of the device makes that different analysis options can be provided, adapted towards the specific needs of a patient. Such a personalized approach can consist in the follow-up of snoring features [7], or in the determination of a person’s architecture of the night [5].

In order to promote the device in view of participatory healthcare, its use should be beneficial for both the patient and the medical specialist. In using the device the measurements are performed in the home setting of a patient ensuring reliable relevant data collection, which is essential for decision making. In addition long term repeated monitoring can be obtained. In case of simple snoring the device can measure snoring to obtain longitudinal information over weeks in view of the patient’s (or partners) complaining.