The three proposed classifiers showed good performance in the discrimination of skills, especially when information from all MAPs and tasks combined were considered. A correlation between the surgeons’ previous experience and their execution of the tasks could be ascertained from results. However, misclassifications across all the classifiers could imply the existence of other factors influencing psychomotor competence.

The present paper describes a system for older people to self-administer the 30-s chair stand test (CST) at home without supervision. The system comprises a low-cost sensor to count sit-to-stand (SiSt) transitions, and an Android application to guide older people through the procedure. Two observational studies were conducted to test (i) the sensor in a supervised environment (n = 7; m = 83.29 years old, sd = 4.19; 5 female), and (ii) the complete system in an unsupervised one (n = 7; age 64–74 years old; 3 female). The participants in the supervised test were asked to perform a 30-s CST with the sensor, while a member of the research team manually counted valid transitions. Automatic and manual counts were perfectly correlated (Pearson’s r = 1, p = 0.00). Even though the sample was small, none of the signals around the critical score were affected by harmful noise; p (harmless noise) = 1, 95% CI = (0.98, 1). The participants in the unsupervised test used the system in their homes for a month. None of them dropped out, and they reported it to be easy to use, comfortable, and easy to understand. Thus, the system is suitable to be used by older adults in their homes without professional supervision.

Lower-limb strength is a marker of functional decline in elders. This work studies the feasibility of using the quasi-periodic nature of the distance between a subjects’ back and the chair backrest during a 30-s chair–stand test (CST) to carry out unsupervised measurements based on readings from a low-cost ultrasound sensor. The device comprises an ultrasound sensor, an Arduino UNO board, and a Bluetooth module. Sit-to-stand transitions are identified by filtering the signal with a moving minimum filter and comparing the output to an adaptive threshold. An inter-rater reliability (IRR) study was carried out to validate the device ability to count the same number of valid transitions as the gold-standard manual count. A group of elders (age: mean (m) = 80.79 years old, SD = 5.38; gender: 21 female and seven male) were asked to perform a 30-s CST using the device while a trained nurse manually counted valid transitions. Ultimately, a moving minimum filter was necessary to cancel the effect of outliers, likely produced because older people tend to produce more motion artefacts and, thus, noisier signals. While the intra-class correlation coefficient (ICC) for this study was good (ICC = 0.86, 95% confidence interval (CI) = 0.73, 0.93), it is not yet clear whether the results are sufficient to support clinical decision-making.

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