DESIGN: In-depth and focus group interviews were conducted with participants who have engaged in telemedicine. Questions included were participants' perception on the programme being used, satisfaction as well as engagement with the telemedicine programme. All interviews and focus groups were audio-recorded and transcribed verbatim. Data were analysed using a thematic approach.

PARTICIPANTS AND SETTING: People with type 2 diabetes (n=48) who participated in a randomised controlled study which examined the use of telemedicine for diabetes management were recruited from 11 primary care clinics located within the Klang Valley.

RESULTS: Twelve focus groups and two in-depth interviews were conducted. Four themes emerged from the analysis: (1) generational difference; (2) independence and convenience, (3) sharing of health data and privacy and (4) concerns and challenges. The main obstacles found in patients using the telemedicine systems were related to internet connectivity and difficulties experienced with system interface. Cost was also another significant concern raised by participants. Participants in this study were primarily positive about the benefits of telemedicine, including its ability to provide real-time data and disease monitoring and the reduction in clinic visits.

Material and method: Computer-assisted total knee arthroplasty (TKA) or primary osteoarthritis of the knee was performed in 51 knees in 36 patients with a mean age of 69.51 years. All procedures were performed by a single surgeon using the same implant design. The intraclass correlation coefficient (ICC) was used to compare the intra-operative CAN-FRA with the post-operative CT-FRA. The angle between the anatomical epicondylar axis and the posterior condylar axis of the implant (CT-FRA) was measured at two separate timepoints by three observers who were blinded to the intra-operative CAN-FRA. Internal rotation was defined as rotation in the negative direction, while external rotation was defined as positive.

Results: The mean intra-operative CAN-FRA was 0.1° ± 2.8° (range -5.0° to 5.5°). The mean post-operative CT-FRA was -1.3° ± 2.1° (range -4.6° to 4.4°). The mean difference between the CAN-FRA and the CT-FRA was -1.3° ± 2.2° (range -7.9° to 2.4°). The respective ICC values for the three observers were 0.92, 0.94, and 0.93, while the respective intra-observer coefficients were 0.91, 0.85, and 0.90. The ICC for the intra-operative CAN-FRA versus the post-operative CT-FRA was 0.71.

OBJECTIVE: This paper aimed to describe the development process of the COVID-19 Symptom Monitoring System (CoSMoS), which consists of a self-monitoring, algorithm-based Telegram bot and a teleconsultation system. We describe all the essential steps from the clinical perspective and our technical approach in designing, developing, and integrating the system into clinical practice during the COVID-19 pandemic as well as lessons learned from this development process.

METHODS: CoSMoS was developed in three phases: (1) requirement formation to identify clinical problems and to draft the clinical algorithm, (2) development testing iteration using the agile software development method, and (3) integration into clinical practice to design an effective clinical workflow using repeated simulations and role-playing.

RESULTS: We completed the development of CoSMoS in 19 days. In Phase 1 (ie, requirement formation), we identified three main functions: a daily automated reminder system for patients to self-check their symptoms, a safe patient risk assessment to guide patients in clinical decision making, and an active telemonitoring system with real-time phone consultations. The system architecture of CoSMoS involved five components: Telegram instant messaging, a clinician dashboard, system administration (ie, back end), a database, and development and operations infrastructure. The integration of CoSMoS into clinical practice involved the consideration of COVID-19 infectivity and patient safety.

Objective: This study aimed to perform a systematic review to describe the achievements made by the researchers, summarizing findings that have been found by previous researchers in feature extraction and CTG classification, to determine criteria and evaluation methods to the taxonomies of the proposed literature in the CTG field and to distinguish aspects from relevant research in the field of CTG.

Methods: Article search was done systematically using three databases: IEEE Xplore digital library, Science Direct, and Web of Science over a period of 5 years. The literature in the medical sciences and engineering was included in the search selection to provide a broader understanding for researchers.

Results: After screening 372 articles, and based on our protocol of exclusion and inclusion criteria, for the final set of articles, 50 articles were obtained. The research literature taxonomy was divided into four stages. The first stage discussed the proposed method which presented steps and algorithms in the pre-processing stage, feature extraction and classification as well as their use in CTG (20/50 papers). The second stage included the development of a system specifically on automatic feature extraction and CTG classification (7/50 papers). The third stage consisted of reviews and survey articles on automatic feature extraction and CTG classification (3/50 papers). The last stage discussed evaluation and comparative studies to determine the best method for extracting and classifying features with comparisons based on a set of criteria (20/50 articles).

Discussion: This study focused more on literature compared to techniques or methods. Also, this study conducts research and identification of various types of datasets used in surveys from publicly available, private, and commercial datasets. To analyze the results, researchers evaluated independent datasets using different techniques.