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Background A reduction in the number of face-to-face medical examinations conducted for patients with noncommunicable diseases (NCDs) during the first wave of the COVID-19 pandemic has led to health care professionals quickly adopting different strategies to communicate with and monitor their patients. Such strategies include the increased use of digital health tools. However, patient preferences, privacy concerns, a lack of regulations, overregulation, and insufficient evidence on the efficacy of digital health tools may have hampered the potential positive benefits of using such tools to manage NCDs. Objective This viewpoint aims to discuss the views of an advisory board of patient and caregiver association members. Specifically, we aim to present this advisory board’s view on the role of digital health tools in managing patients with NCDs during and after the COVID-19 pandemic, and to identify future directions based on patients’ perspectives. Methods As an initiative under the NCD Partnership (PARTners in Ncds Engage foR building Strategies to improve Healthy ageing In Patients) model of Upjohn, a web-based advisory board of patient and caregiver advocates was held on July 28, 2020, to bring together key stakeholders from public and private sectors. Results The following key themes emerged: (1) technology developers should understand that the goals of patients may differ from those of health care professionals and other stakeholders; (2) patients, health care professionals, caregivers, and other end users need to be involved in the development of digital health tools at the earliest phase possible, to guarantee usability, efficacy, and adoption; (3) digital health tools must be better tailored to people with complex conditions, such as multimorbidity, older age, and cognitive or sensory impairment; and (4) some patients do not want or are unable to use digital health care tools, so adequate alternatives should always be available. Conclusions There was consensus that public-private partnership models, such as the Upjohn NCD Partnership, can be effective models that foster innovation by integrating multiple perspectives (eg, patients’ perspectives) into the design, development, and implementation of digital and nondigital health tools, with the main overall objective of improving the life of patients with NCDs.

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This paper considers the online localization of sick animals in pig houses. It presents an automated online recognition and localization procedure for sick pig cough sounds. The instantaneous energy of the signal is initially used to detect and extract individual sounds from a continuous recording and their duration is used as a preclassifier. Autoregression (AR) analysis is then employed to calculate an estimate of the sound signal, and the parameters of the estimated signal are subsequently evaluated to identify the sick cough sounds. It is shown that the distribution of just three AR parameters provides an adequate classifier for sick pig coughs. A localization technique based on the time difference of arrival is evaluated on field data and is shown that it is of acceptable accuracy for this particular application. The algorithm is applied on continuous recordings from a pig house to evaluate its effectiveness. The correct identification ratio ranged from 73% (27% false positive identifications) to 93% (7% false positive identifications) depending on the position of the microphone that was used for the recording. Although the false negative identifications are about 50% it is shown that this accuracy can be enough for the purpose of this tool. Finally, it is suggested that the presented application can be used to online monitor the welfare in a pig house, and provide early diagnosis of a cough hazard and faster treatment of sick animals.