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Nowadays, wearable wireless devices represent an exciting challenge both for controlling one's lifestyle and for specific applications like telemedicine and at-home healthcare monitoring. Many low-cost sensors and sensor systems are currently on the market, but only a limited number of them are validated and certified for clinical applications. This paper presents preliminary results of the accuracy assessment of an electrocardiography (ECG) device for cardiovascular disease monitoring that will be applied by the patients for self-checking. In particular, the analog front end integrated circuit MAX30001 is proposed and tested, while the principal features of MAX30001 evaluation board software were described, as well as three cardiac pathologies which require in-depth and continuous ECG monitoring. An accuracy setup was realized to evaluate the acquisition fidelity; it is based on a high-quality waveform generator that imposes to the MAX30001 two different periodic signals: a sine and a sinc with the frequency of 1 Hz to 10 Hz with a 5 Hz step. The accuracy evaluation shows how the integrated circuit provides a normalized root mean square error in the chosen frequency range, lower than 0.01 and lower than 0.20, respectively, for the sine and sinc waveform. Moreover, it presents for sinc signal a peak detection rate of 80%.

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by early impairment in social and communication domains and autonomic nervous system unbalance. This study evaluated heart rate (HR) as a possible indicator of stress response in children with ASD as compared to children with language disorder (LD). Twenty-four patients [mean age = 42.62 months; SD = 8.14 months,12 with ASD (10 M/2F) and 12 with LD (8 M/4F)] underwent clinical [Leiter International Performance Scale-Revised, Autism Diagnostic Observation Schedule, second edition (ADOS-2)] and physiological evaluation (HR monitoring) during five interactive activities, while wearing an HR measurement device. IQ (ASD:IQ = 103.33 ± 12.85 vs. LD:IQ = 111.00 ± 8.88, p = 0.103) and fluid reasoning on the Leiter-R Scale were within the normal range in all subjects. Increased HR during the third activity (ADOS-2 bubble play) significantly correlated with autistic symptoms (r = 0.415; p = 0.044), while correlations between ADOS-2 total score and HR during the first activity (ADOS-2 free play; r = 0.368; p = 0.077), second activity (Leiter-R figure ground subscale; r = 0.373, p = 0.073), and fifth activity (ADOS-2 anticipation of a routine with objects; r = 0.368; p = 0.076) did not quite reach statistical significance. Applying a linear regression model, we found that the ADOS-2 total score significantly influenced HR variations (p = 0.023). HR monitoring may provide a better understanding of the stress-provoking situations for children with ASD. Furthermore, it could help clinicians detect the impact of the stressful condition on the autistic core and adress treatment strategy.

Wireless Sensor Network (WSN) has been adopted in many contexts, such as healthcare or industry. In museum scenarios, WSN has been introduced for environmental monitoring, to control temperature and relative humidity. Nowadays, the development of low-cost micro-scale sensing units, opened to new possibilities for WSN development, enlarging the set of feasible measurements to gaseous pollutant concentration, relative humidity, temperature, light intensity, air flow, or vibration.This work is part of the overarching goal of developing a low-cost and minimally invasive WSN designed for a museum scenario. The proposed WSN node, based on a ZigBee standard, gathers signals provided by: a 9-axis MIMU, a sensor for temperature and relative humidity, and three gas detection boards. In this paper, specifically, we present performances of the WSN node in detecting: structure tilt, vibrations, and daily cycle of humidity, temperature, and gas deposition.