RESUMO
The rising prevalence of Parkinson's disease (PD) globally presents a significant public health challenge for national healthcare systems, particularly in low-to-middle income countries, such as Thailand, which may have insufficient resources to meet these escalating healthcare needs. There are also many undiagnosed cases of early-stage PD, a period when therapeutic interventions would have the most value and least cost. The traditional "passive" approach, whereby clinicians wait for patients with symptomatic PD to seek treatment, is inadequate. Proactive, early identification of PD will allow timely therapeutic interventions, and digital health technologies can be scaled up in the identification and early diagnosis of cases. The Parkinson's disease risk survey (TCTR20231025005) aims to evaluate a digital population screening platform to identify undiagnosed PD cases in the Thai population. Recognizing the long prodromal phase of PD, the target demographic for screening is people aged ≥ 40 years, approximately 20 years before the usual emergence of motor symptoms. Thailand has a highly rated healthcare system with an established universal healthcare program for citizens, making it ideal for deploying a national screening program using digital technology. Designed by a multidisciplinary group of PD experts, the digital platform comprises a 20-item questionnaire about PD symptoms along with objective tests of eight digital markers: voice vowel, voice sentences, resting and postural tremor, alternate finger tapping, a "pinch-to-size" test, gait and balance, with performance recorded using a mobile application and smartphone's sensors. Machine learning tools use the collected data to identify subjects at risk of developing, or with early signs of, PD. This article describes the selection and validation of questionnaire items and digital markers, with results showing the chosen parameters and data analysis methods to be robust, reliable, and reproducible. This digital platform could serve as a model for similar screening strategies for other non-communicable diseases in Thailand.
RESUMO
The decoding multivariate Temporal Response Function (decoder) or speech envelope reconstruction approach is a well-known tool for assessing the cortical tracking of speech envelope. It is used to analyse the correlation between the speech stimulus and the neural response. It is known that auditory late responses are enhanced with longer gaps between stimuli, but it is not clear if this applies to the decoder, and whether the addition of gaps/pauses in continuous speech could be used to increase the envelope reconstruction accuracy. We investigated this in normal hearing participants who listened to continuous speech with no added pauses (natural speech), and then with short (250 ms) or long (500 ms) silent pauses inserted between each word. The total duration for continuous speech stimulus with no, short, and long pauses were approximately, 10 minutes, 16 minutes, and 21 minutes, respectively. EEG and speech envelope were simultaneously acquired and then filtered into delta (1-4 Hz) and theta (4-8 Hz) frequency bands. In addition to analysing responses to the whole speech envelope, speech envelope was also segmented to focus response analysis on onset and non-onset regions of speech separately. Our results show that continuous speech with additional pauses inserted between words significantly increases the speech envelope reconstruction correlations compared to using natural speech, in both the delta and theta frequency bands. It also appears that these increase in speech envelope reconstruction are dominated by the onset regions in the speech envelope. Introducing pauses in speech stimuli has potential clinical benefit for increasing auditory evoked response detectability, though with the disadvantage of speech sounding less natural. The strong effect of pauses and onsets on the decoder should be considered when comparing results from different speech corpora. Whether the increased cortical response, when longer pauses are introduced, reflect improved intelligibility requires further investigation.