Smartphone-Based Real-time Assessment of Swallowing Ability From the Swallowing Sound

Abstract

Dysphagia can cause serious challenges to both physical and mental health. Aspiration due to dysphagia is a major health risk that could cause pneumonia and even death. The videofluoroscopic swallow study (VFSS), which is considered the gold standard for the diagnosis of dysphagia, is not widely available, expensive and causes exposure to radiation. The screening tests used for dysphagia need to be carried out by trained staff, and the evaluations are usually non-quantifiable. This paper investigates the development of the Swallowscope, a smartphone-based device and a feasible real-time swallowing sound-processing algorithm for the automatic screening, quantitative evaluation, and the visualisation of swallowing ability. The device can be used during activities of daily life with minimal intervention, making it potentially more capable of capturing aspirations and risky swallow patterns through the continuous monitoring. It also consists of a cloud-based system for the server-side analyzing and automatic sharing of the swallowing sound. The real-time algorithm we developed for the detection of dry and water swallows is based on a template matching approach. We analyzed the wavelet transformation-based spectral characteristics and the temporal characteristics of simultaneous synchronised VFSS and swallowing sound recordings of 25% barium mixed 3-ml water swallows of 70 subjects and the dry or saliva swallowing sound of 15 healthy subjects to establish the parameters of the template. With this algorithm, we achieved an overall detection accuracy of 79.3% (standard error: 4.2%) for the 92 water swallows; and a precision of 83.7% (range: 66.6%–100%) and a recall of 93.9% (range: 72.7%–100%) for the 71 episodes of dry swallows.

An ultrathin conformable vibration-responsive electronic skin for quantitative vocal recognition

“…4a, the device exhibits a high and linear sensitivity of 5.5 V Pa −1 at these voice frequencies and all voice pressures: this performance represents an outstanding improvement over that of the flexible vibration sensors reported so far, which cannot recognize variations in vocal patterns and loudness due to their non-flat frequency response and insufficient sensitivity. Furthermore, our device exhibits voice-recognition ability that is comparable to that of commercial microphone systems including throat microphones 36 . The performance of our device is maintained on neck skin surfaces due to its skin conformity.…”

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Biosensors for Personal Mobile Health: A System Architecture Perspective

“…However, when tested with real patients, these metrics decreased. In another work, Jayatilake et al developed a device for automatic analysis of swallowing sounds for dysphagia diagnosis . The device uses a neck‐worn microphone to record the swallowing sound which is then processed using an on‐phone algorithm for detection of both dry and wet swallows.…”