We discuss health monitoring as a potential application field for wearable sensors. We present some usage models for health monitoring and discuss the technical requirements for the health-monitoring system based on wearable and ambient sensors, which measure health-related data in daily environments of the users or patients. The presentation is by no means complete, but it aims to give an idea of the system-level issues to be considered for real applications. The technology in this area is rapidly developing, and without doubt we will evidence emergence of these applications in the coming years in the market.

Inadequate analgesia during general anaesthesia may present as undesirable haemodynamic responses. No objective measures of the adequacy of analgesia exist. We aimed at developing a simple numerical measure of the level of surgical stress in an anaesthetized patient. Sixty and 12 female patients were included in the development and validation data sets, respectively. All patients had elective surgery with propofol–remifentanil target controlled anaesthesia. Finger photoplethysmography and electrocardiography waveforms were recorded throughout anaesthesia and various waveform parameters were extracted off-line. Total surgical stress (TSS) for a patient was estimated based on stimulus intensity and remifentanil concentration. The surgical stress index (SSI) was developed to correlate with the TSS estimate in the development data set. The performance of SSI was validated within the validation data set during and before surgery, especially at skin incision and during changes of the predicted remifentanil effect-site concentration. SSI was computed as a combination of normalized heart beat interval (HBI_norm) and plethysmographic pulse wave amplitude (PPGA_norm): SSI = 100–(0.7*PPGA_norm+0.3*HBI_norm). SSI increased at skin incision and stayed higher during surgery than before surgery; SSI responded to remifentanil concentration changes and was higher at the lower concentrations of remifentanil. SSI reacts to surgical nociceptive stimuli and analgesic drug concentration changes during propofol–remifentanil anaesthesia. Further validation studies of SSI are needed to elucidate its usefulness during other anaesthetic and surgical conditions.

Research on decision support applications in healthcare, such as those related to diagnosis, prediction, treatment planning, etc., has seen strongly growing interest in recent years. This development is thanks to the increase in data availability as well as to advances in artificial intelligence and machine learning research and access to computational resources. Highly promising research examples are published daily. However, at the same time, there are some unrealistic, often overly optimistic, expectations and assumptions with regard to the development, validation and acceptance of such methods. The healthcare application field introduces requirements and potential pitfalls that are not immediately obvious from the 'general data science' viewpoint. Reliable, objective, and generalisable validation and performance assessment of developed data-analysis methods is one particular pain-point. This may lead to unmet schedules and disappointments regarding true performance in real-life with as result poor uptake (or non-uptake) at the end-user side. It is the aim of this tutorial to provide practical guidance on how to assess performance reliably and efficiently and avoid common traps especially when dealing with application for health and wellness settings. Instead of giving a list of do's and don't s, this tutorial tries to build a better understanding behind these issues and presents both the most relevant performance evaluation criteria as well as approaches how to compute them. Along the way, we will indicate common mistakes and provide references discussing various topics more in-depth.

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet

To assess whether standardized handwriting can provide quantitative measures to distinguish patients diagnosed with Parkinson's disease from age- and gender-matched healthy control participants. Exploratory study. Pen tip trajectories were recorded during circle, spiral and line drawing and repeated character ‘elelelel’ and sentence writing, performed by Parkinson patients and healthy control participants. Parkinson patients were tested after overnight withdrawal of anti-Parkinsonian medication. University Medical Center Groningen, tertiary care, the Netherlands. Patients with Parkinson's disease (n = 10; mean age 69.0 years; 6 male) and healthy controls (n = 10; mean age 68.1 years; 6 male). Not applicable. Movement time and velocity to detect bradykinesia and the size of writing to detect micrographia. A rest recording to investigate the presence of a rest-tremor, by frequency analysis. Mean disease duration in the Parkinson group was 4.4 years and the patients were in modified Hoehn-Yahr stages 1–2.5. In general, Parkinson patients were slower than healthy control participants. Median time per repetition, median velocity and median acceleration of the sentence task and median velocity of the elel task differed significantly between Parkinson patients and healthy control participants (all p<0.0014). Parkinson patients also wrote smaller than healthy control participants and the width of the ‘e’ in the elel task was significantly smaller in Parkinson patients compared to healthy control participants (p<0.0014). A rest-tremor was detected in the three patients who were clinically assessed as having rest-tremor. This study shows that standardized handwriting can provide objective measures for bradykinesia, tremor and micrographia to distinguish Parkinson patients from healthy control participants.