Neurodegenerative disorders (NDDs) constitute an increasing global burden and can significantly impair an individual’s mobility, physical activity (PA), and independence. Remote monitoring has been difficult without relying on diaries/questionnaires which are more challenging for people with dementia to complete. Wearable global positioning system (GPS) sensors and accelerometers present a cost-effective and noninvasive way to passively monitor mobility and PA. In addition, changes in sensor-derived outcomes (such as walking behaviour, sedentary, and active activity) may serve as potential biomarkers of disease onset, progression, and response to treatment. We performed a systematic search across four databases to identify papers published within the past 5 years, in which wearable GPS or accelerometers were used to monitor mobility or PA in patients with common NDDs (Parkinson’s disease, Alzheimer’s disease, motor neuron diseases/amyotrophic lateral sclerosis, vascular parkinsonism, and vascular dementia). Disease and technology-specific vocabulary were searched singly, and then in combination, identifying 4985 papers. Following deduplication, we screened 3115 papers and retained 28 studies following a full text review. One study used wearable GPS and accelerometers, while 27 studies used solely accelerometers in NDDs. GPS-derived measures had been validated against current gold standard measures in one Parkinson’s cohort, suggesting that the technology may be applicable to other NDDs. In contrast, accelerometers are widely utilised in NDDs and have been operationalised in well-designed clinical trials.

One of the major challenges for blind and visually impaired (BVI) people is traveling safely to cross intersections on foot. Many countries are now generating audible signals at crossings for visually impaired people to help with this problem. However, these accessible pedestrian signals can result in confusion for visually impaired people as they do not know which signal must be interpreted for traveling multiple crosses in complex road architecture. To solve this problem, we propose an assistive system called CAS (Crossing Assistance System) which extends the principle of the BLE (Bluetooth Low Energy) RSSI (Received Signal Strength Indicator) signal for outdoor and indoor location tracking and overcomes the intrinsic limitation of outdoor noise to enable us to locate the user effectively. We installed the system on a real-world intersection and collected a set of data for demonstrating the feasibility of outdoor RSSI tracking in a series of two studies. In the first study, our goal was to show the feasibility of using outdoor RSSI on the localization of four zones. We used a k-nearest neighbors (kNN) method and showed it led to 99.8% accuracy. In the second study, we extended our work to a more complex setup with nine zones, evaluated both the kNN and an additional method, a Support Vector Machine (SVM) with various RSSI features for classification. We found that the SVM performed best using the RSSI average, standard deviation, median, interquartile range (IQR) of the RSSI over a 5 s window. The best method can localize people with 97.7% accuracy. We conclude this paper by discussing how our system can impact navigation for BVI users in outdoor and indoor setups and what are the implications of these findings on the design of both wearable and traffic assistive technology for blind pedestrian navigation.

The spacesuit, particularly the spacesuit glove, creates a barrier between astronauts and their environment. Motivated by the vision of facilitating full-body immersion for effortless space exploration, it is necessary to understand the sensory needs of astronauts during extra-vehicular activities (EVAs). In this paper, we present the outcomes from a two-week field study performed at the Mars Desert Research Station, a facility where crews carry out Mars-simulated missions. We used a combination of methods (a haptic logbook, technology probes, and interviews) to investigate user needs for haptic feedback in EVAs in order to inform the design of a haptic glove. Our results contradict the common belief that a haptic technology should always convey as much information as possible, but should rather offer a controllable transfer. Based on these findings, we identified two main design requirements to enhance haptic feedback through the glove: (i) transfer of the shape and pressure features of haptic information and (ii) control of the amount of haptic information. We present the implementation of these design requirements in the form of the concept and first prototype of ExoSkin. ExoSkin is a morphing haptic feedback layer that augments spacesuit gloves by controlling the transfer of haptic information from the outside world onto the astronauts’ skin.

Soft robotics is used in real-world clinical situations, including surgery, rehabilitation, and diagnosis. However, several challenges remain to make soft robots more viable, especially for clinical interventions such as improving sleep quality, which impacts physiological and mental health. This paper presents an autoethnographic account of the experience of sleeping with a companion robot (Somnox), which mimics breathing to promote better sleep. The study is motivated by the key author’s experience with insomnia and a desire to better understand how Somnox is used in different social contexts. Data were collected through diary entries for 16 weeks (8 weeks without, 8 weeks with) and analysed thematically. The findings indicate improved sleep and observations about the relationship developed with the companion robot, including emotional connection and empathy for the technology. Furthermore, Somnox is a multidimensional family companion robot that can ease stomach discomfort and stress, reduce anxiety, and provide holistic care.