Validity and usability of a smart ball-driven serious game to monitor grip strength in independent elderlies.

Telemonitoring is one of the most expedient answers to the strong need for preventive care imposed by the rapidly aging society. We propose an innovative solution to the detection of early signs of frailty by presenting a serious game controlled by a smart sensorized soft plastic ball, designed to achieve continuous home-based monitoring of muscle weakness in older adults. Design, development, and testing of the smart ball and of the game interface devised to guide the monitoring procedure are presented. Reliability and concurrent validity of the system in measuring maximal grip strength against the clinical standard Jamar® were evaluated. Serious game usability and acceptance were investigated on 26 elderlies. Smart ball and Jamar measurements were well correlated (0.76 and 0.80 for dominant and non-dominant hands) and test-retest reliability of pressure measurements was excellent (intraclass correlation coefficient >0.94). The serious game was well accepted by the 96.1 percent of participants, who provided a strongly positive usability score (87.7/100). The smart ball-driven serious game demonstrated excellent reliability and good validity in measuring grip strength. The proposed smart ball-driven serious game can be used for home self-monitoring of grip strength in elderlies.

Wearable monitoring devices for assistive technology: case studies in post-polio syndrome.

The correct choice and customization of an orthosis are crucial to obtain the best comfort and efficiency. This study explored the feasibility of a multivariate quantitative assessment of the functional efficiency of lower limb orthosis through a novel wearable system. Gait basographic parameters and energetic indexes were analysed during a Six-Minute Walking Test (6-MWT) through a cost-effective, non-invasive polygraph device, with a multichannel wireless transmission, that carried out electro-cardiograph (ECG); impedance-cardiograph (ICG); and lower-limb accelerations detection. Four subjects affected by Post-Polio Syndrome (PPS) were recruited. The wearable device and the semi-automatic post-processing software provided a novel set of objective data to assess the overall efficiency of the patient-orthosis system. Despite the small number of examined subjects, the results obtained with this new approach encourage the application of the method thus enlarging the dataset to validate this promising protocol and measuring system in supporting clinical decisions and out of a laboratory environment.

Automatic detection of tic activity in the Tourette Syndrome.

This study presents a simple decision-support system for the detection of tic events during the Tourette Syndrome (TS). The system is based on a triaxial accelerometer placed on the patient's trunk. TS is a neurological disorder that emerges during childhood and that is characterized by a large spectrum of involuntary/compulsive movements and sounds. 12 subjects with chronic TS participated in the study and the tic events were both measured by the proposed device and visually classified through video recording. 3D-acceleration timeseries were combined through a module operator and their noise was eliminated by a median filter. Signal to noise ratio was improved by a nonlinear energy operator. Finally, a time-variant threshold was used to detect tic events. The automatic tic recognition showed a performance around 80 % in terms of sensitivity, specificity and accuracy. In conclusion, this simple, automatic and unobtrusive method offers an alternative approach to quantitatively assess the tic events in clinical and non clinical environments. This overcomes the limitations of the current motor tic evaluation which is done by clinical observation and/or video-inspection in specialized neurological centres.

Prototype of a wearable system for remote fetal monitoring during pregnancy.

Fetal Heart Rate (FHR) monitoring gives important information about the fetus health state during pregnancy. This paper presents a new prototype for remote fetal monitoring. The device will allow to monitor FHR in a domiciliary context and to send fetal ECG traces to a hospital facility, where clinicians can interpret them. In this way the mother could receive prompt feedback about fetal wellbeing. The system is characterized by two units: (i) a wearable unit endowed with textile electrodes for abdominal ECG recordings and with a Field Programmable Gate Array (FPGA) board for fetal heart rate (FHR) extraction; (ii) a dock station for the transmission of the data through the telephone line. The system will allow to reduce costs in fetal monitoring, improving the assessment of fetal conditions. The device is actually in development state. In this paper, the most crucial aspects behind its fulfillment are discussed.

A novel automatic method for monitoring Tourette motor tics through a wearable device.

The aim of this study was to propose a novel automatic method for quantifying motor-tics caused by the Tourette Syndrome (TS). In this preliminary report, the feasibility of the monitoring process was tested over a series of standard clinical trials in a population of 12 subjects affected by TS. A wearable instrument with an embedded three-axial accelerometer was used to detect and classify motor tics during standing and walking activities. An algorithm was devised to analyze acceleration data by: eliminating noise; detecting peaks connected to pathological events; and classifying intensity and frequency of motor tics into quantitative scores. These indexes were compared with the video-based ones provided by expert clinicians, which were taken as the gold-standard. Sensitivity, specificity, and accuracy of tic detection were estimated, and an agreement analysis was performed through the least square regression and the Bland-Altman test. The tic recognition algorithm showed sensitivity = 80.8% ± 8.5% (mean ± SD), specificity = 75.8% ± 17.3%, and accuracy = 80.5% ± 12.2%. The agreement study showed that automatic detection tended to overestimate the number of tics occurred. Although, it appeared this may be a systematic error due to the different recognition principles of the wearable and video-based systems. Furthermore, there was substantial concurrency with the gold-standard in estimating the severity indexes. The proposed methodology gave promising performances in terms of automatic motor-tics detection and classification in a standard clinical context. The system may provide physicians with a quantitative aid for TS assessment. Further developments will focus on the extension of its application to everyday long-term monitoring out of clinical environments.

Pervasive technology in Neonatal Intensive Care Unit: a prototype for newborns unobtrusive monitoring.

Pervasive computing research is introducing new perspectives in a wide range of applications, including healthcare domain. In this study we explore the possibility to realize a prototype of a system for unobtrusive recording and monitoring of multiple biological parameters on premature newborns hospitalized in the Neonatal Intensive Care Unit (NICU). It consists of three different units: a sensitized belt for Electrocardiogram (ECG) and chest dilatation monitoring, augmented with extrinsic transducers for temperature and respiratory activity measure, a device for signals pre-processing, sampling and transmission through Bluetooth(R) (BT) technology to a remote PC station and a software for data capture and post-processing. Preliminary results obtained by monitoring babies just discharged from the ward demonstrated the feasibility of the unobtrusive monitoring on this kind of subjects and open a new scenario for premature newborns monitoring and developmental cares practice in NICU.

A Wearable Home BCI system: preliminary results with SSVEP protocol.

This paper presents and discusses the realization and the performances of a wearable system for EEG-based BCI applications. The system (called Kimera) consists of a two-layer hardware architecture (the wireless acquisition and transmission board based on a Bluetooth ® ARM chip, and a low power miniaturized biosignal acquisition analog front end) together with a software suite (called Bellerophonte) for the Graphic User Interface management, protocol execution, data recording, transmission and processing. The implemented BCI system was based on the SSVEP protocol, applied to a two state selection by using standards display/monitor with a couple of high efficiency LEDs. The frequency features of the signal were computed and used in the intention detection. The BCI algorithm is based on a supervised classifier implemented through a multi-class Canonical Discriminant Analysis (CDA) with a continuous realtime feedback based on the mahalanobis distance parameter. Five healthy subjects participated in the first phase for a preliminary device validation. The obtained results are very interesting and promising, being lined out to the most recent performance reported in literature with a significant improvement both in system and in classification capabilities. The user-friendliness and low cost of the Kimera& Bellerophonte platform make it suitable for the development of home BCI applications.