Back pain is one of the largest drivers of workplace injury and lost productivity in industries around the world. Back injuries were one of the leading reasons in resulting in days away from work at 38.5% across all occupations, increasing for manual laborers to 43%. While the cause of the back pain can vary across occupations, for materiel movers it is often caused from repetitive poor lifting. To reduce the issues, the Aerial Porter Exoskeleton (APEx) was created. The APEx uses a hip-mounted, powered exoskeleton attached to an adjustable vest. An onboard computer calculates the configuration of the user to determine when to activate. Lift form is assisted by using a novel lumbar brace mounted on the sides of the hips. Properly worn, the APEx holds the user upright while providing additional hip torque through a lift. This was tested by having participants complete a lifting test with the exoskeleton worn in the “on” configuration compared with the exoskeleton not worn. The APEx has been shown to deliver 30 Nm of torque in lab testing. The activity recognition algorithm has also been shown to be accurate in 95% of tested conditions. When worn by subjects, testing has shown average peak reductions of 14.9% BPM, 8% in VO2 consumption, and an 8% change in perceived effort favoring the APEx.

We present two practice-situated participatory investigations using networked wearable sensors to develop movement-responsive collectively playable musical instruments: a series of four collocated workshops for expert dancers and a distance learning course in which students use wearable technology to enhance embodied learning and feelings of connectedness telematically. We reflect on our exploration of techniques for structuring ensemble improvisations augmented with bespoke digital musical instruments using aggregate statistical measures, such as variance of participants’ physical orientation as an index of group intention. Participatory design exchanges top-down design methodologies with bottom-up approaches consulting actors’ interests. We follow this approach by evolving our instruments through abductive experiments and trial-and-error tinkering, without strong theories, methods, or models, using elementary signal processing techniques that are meaningfully understood and modified by participants. Our experiences suggest useful scaffolding techniques for educational transdisciplinary research-creation communities seeking to explore relational ensemble dynamics in telematic and/or physically collocated settings using accessible wearable technologies. Through creative inquiry and participation, technical objects can become bearers of sense and meaning rather than instating mystifying or alienating relations for the participants.

The performative installation DeviceD utilizes a network of systems toward facilitating interaction between dancer, digital media, and audience. Central to the work is a wearable haptic feedback system able to wirelessly deliver vibrotactile stimuli, with the latter initiated by the audience through posting on Twitter social media platform; the system in use searches for specific mentions, hashtags, and keywords, with positive results causing the system to trigger patterns of haptic biofeedback across the wearable’s four actuator motors. The system acts as the intermediator between the audience’s online actions and the dancer receiving physical stimuli; the dancer interprets these biofeedback signals according to Laban’s Effort movement qualities, with the interpretation informing different states of habitual and conscious choreographic performance. In this article, the authors reflect on their collaborative process while developing DeviceD alongside a multidisciplinary team of technologists, detailing their experience of refining the technology and methodology behind the work while presenting it in three different settings. A literature review is used to situate the work among contemporary research on interaction over internet and haptics in performance practice; haptic feedback devices have been widely used within artistic work for the past 25 years, with more recent practice and research outputs suggesting an increased interest for haptics in the field of dance research. The authors detail both technological and performative elements making up the work, and provide a transparent evaluation of the system, as means of providing a foundation for further research on wearable haptic devices.

Climbing stairs can become a daily obstacle for elderly people, and an exoskeleton can assist here. However, the exoskeletons that are designed to assist stair climbing are actuated in different ways. To find a minimal actuation configuration, we identify the assist phases by evaluating the power deficit of 11 healthy but weak elderly people (72.4 ± 2.1 years; 69–76 years; 1.67 ± 0.10 m; 74.88 ± 14.54 kg) compared to 13 younger people (24.0 ± 1.8 years; 22–28 years; 1.74 ± 0.10 m; 70.85 ± 11.91 kg) in a biomechanical study and discuss moment characteristics. Three-dimensional kinematics and ground reaction forces were collected, and kinematics, kinetics, and power characteristics of each subject for ascent and descent were calculated using inverse dynamics. Significant differences for power between both groups were assessed with statistical parametric mapping method using dynamic time warping. During ascent, the largest significant power deficit of the elderly subjects occurs in the single stance phase (SSP) during pull-up in the knee joint. During descent, significant mean power deficits of 0.2 and 0.8 W/kg for the highest deficit occur in the ankle joint in the beginning of the SSP and also in the knee joint in the same phase. Therefore, an exoskeleton should address the power deficit for knee extension (ascent: 1.0 ± 0.9 W/kg; descent: 0.3 ± 0.2 W/kg) and could assist the ankle during ascent and descent by an additional plantar flexion moment of 0.2 Nm/kg each.

Gesture-based musical performance with on-body sensing represents a particular case of wearable connection. Gloves and hand-sensing interfaces connected to real-time digital sound production and transformation processes enable empty-handed, expressive musical performance styles. In this article, the origins and developments of this practice as well as a specific use case are investigated. By taking the technical, cognitive, and cultural dimensions of this media performance as foundation, a reflection on the value, limitations, and opportunities of computational approaches to movement translation and analysis is carried out. The insights uncover how the multilayered, complex artistic situations produced by these performances are rich in intersections and represent potent amplifiers for investigating corporeal presence and affective engagement. This allows to identify problems and opportunities of existing research approaches and core issues to be solved in the domain of movement, music, interaction technology, and performance research.

This paper proposes a novel origami-inspired adult diaper design that improves discretion by reducing sag and increasing wicking across the entire diaper pad. While other diapers rely on supporting elastics to reduce the sag of the diaper as a whole, this paper proposes an absorbent core that uses liquid activated shaping to take a specified shape. Origami-based folds are also incorporated into the diaper design to increase wicking performance. The paper introduces a disposable compliant mechanism waistband used to deploy the diaper, making it easier to put onto one’s body.

In diabetic peripheral neuropathy, offloading high-plantar-pressure areas using statically offloaded customized insoles or expensive sensors and actuators are commonly-followed treatment procedures. In this article, we propose the concept of dynamically self-offloading therapeutic footwear that operates mechanically without using sensors and actuators. We achieve this by using an array of snapping arches. When a load higher than a bespoke value is applied, these arches enter negative-stiffness regime and offload the high-pressure region by snapping to a different shape. They again return to their initial shape when the load disappears. Thus, they serve as both sensors and actuators that get actuated by person’s body weight. We present an analytical method to compute the switching load and the switchback time of such arches and use them to customize the footwear according to the person’s body weight, gait speed, and foot size. We identify the high-pressure regions from the clinical data and place the arches such that these high-pressure regions get dynamically offloaded, and the pressure gets redistributed to other regions. We considered 200 kPa as a limiting pressure to prevent the prolonged effects of high plantar pressure. To check the efficacy of the concept, a complete 3D-printed prototype made of thermoplastic polyurethane was tested and compared with barefoot and in-shoe plantar pressure for subjects recruited at a clinical facility. We notice that the self-offloading insole shows the plantar pressure reduction at all the foot regions, and significant offloading of 57% is observed at the forefoot region.

The purpose of this study was to determine if estimated center of pressure (COP) from plantar force data collected using three-sensor loadsol insoles was comparable to the COP from plantar pressure data collected using pedar insoles during walking and running. Ten healthy adults walked and ran at self-selected speeds on a treadmill while wearing both a loadsol and pedar insole in their right shoe. Plantar force recorded from the loadsol was used to estimate COP along mediolateral (COPx) and anteroposterior (COPy) axes. The estimated COPx and COPy were compared with the COPx and COPy from pedar using limits of agreement and Spearman’s rank correlation. There were significant relationships and agreement within 5 mm in COPx and 20 mm in COPy between loadsol and pedar at 20–40% of stance during walking and running. However, loadsol demonstrated biases of 7 mm in COPx and 10 mm in COPy compared to pedar near initial contact and toe-off.

The five times sit-to-stand test (FTSS) is an established functional test, used clinically as a measure of lower-limb strength, endurance and falls risk. We report a novel method to estimate and classify cognitive function, balance impairment and falls risk using the FTSS and body-worn inertial sensors. 168 community dwelling older adults received a Comprehensive Geriatric Assessment which included the Mini-Mental State Examination (MMSE) and the Berg Balance Scale (BBS). Each participant performed an FTSS, with inertial sensors on the thigh and torso, either at home or in the clinical environment. Adaptive peak detection was used to identify phases of each FTSS from torso or thigh-mounted inertial sensors. Features were then extracted from each sensor to quantify the timing, postural sway and variability of each FTSS. The relationship between each feature and MMSE and BBS was examined using Spearman’s correlation. Intraclass correlation coefficients were used to examine the intra-session reliability of each feature. A Poisson regression model with an elastic net model selection procedure was used to estimate MMSE and BBS scores, while logistic regression and sequential forward feature selection was used to classify participants according to falls risk, cognitive decline and balance impairment. BBS and MMSE were estimated using cross-validation with low root mean squared errors of 2.91 and 1.50, respectively, while the cross-validated classification accuracies for balance impairment, cognitive decline, and falls risk were 81.96, 72.71, and 68.74%, respectively. The novel methods reported provide surrogate measures which may have utility in remote assessment of physical and cognitive function.

This mixed-methods study investigates the use of wearable technology in embodied psychology research and explores the potential of incorporating bio-signals to focus on the bodily impact of the social experience. The study relies on scientifically established psychological methods of studying social issues, collective relationships and emotional overloads, such as sociodrama, in combination with participant observation to qualitatively detect and observe verbal and nonverbal aspects of social behavior. We evaluate the proposed method through a pilot sociodrama session and reflect on the outcomes. By utilizing an experimental setting that combines video cameras, microphones, and wearable sensors measuring physiological signals, specifically, heart rate, we explore how the synchronization and analysis of the different signals and annotations enables a mixed-method that combines qualitative and quantitative instruments in studying embodied expressiveness and social interaction.

Continuous gait phase plays an important role in robotic prosthesis control. In this paper, we have conducted the offline adaptive estimation (at different speeds and on different ramps) of continuous gait phase of robotic transtibial prosthesis based on the adaptive oscillators. We have used the capacitive sensing method to record the deformation of the muscles. Two transtibial amputees joined in this study. Based on the strain signals of the prosthetic foot and the capacitive signals of the residual limb, the maximum and minimum of estimation errors are 0.80 rad and 0.054 rad, respectively, and their corresponding ratios in one gait cycle are 1.27% and 0.86%, respectively. This paper proposes an effective method to estimate the continuous gait phase based on the capacitive signals of the residual muscles, which provides a basis for the continuous control of robotic transtibial prosthesis.

Previously reported wearable systems for people with Parkinson’s disease (PD) have been focused on the detection of abnormal gait. They suffered from limited accuracy, large latency, poor durability, comfort, and convenience for daily use. Herewith we report an intelligent wearable system (IWS) that can accurately detect abnormal gait in real-time and provide timely cueing for PD patients. The system features novel sensitive, comfortable and durable plantar pressure sensing insoles with a highly compressed data set, an accurate and fast gait algorithm, and wirelessly controlled timely sensory cueing devices. A total of 29 PD patients participated in the first phase without cueing for developing processes of the algorithm, which achieved an accuracy of over 97% for off-line detection of freezing of gait (FoG). In the second phase with cueing, the evaluation of the whole system was conducted with 16 PD subjects via trial and a questionnaire survey. This system demonstrated an accuracy of 94% for real-time detection of FoG and a mean latency of 0.37 s between the onset of FoG and cueing activation. In questionnaire survey, 88% of the PD participants confirmed that this wearable system could effectively enhance walking, 81% thought that the system was comfortable and convenient, and 70% overcame the FoG. Therefore, the IWS makes it an effective, powerful, and convenient tool for enhancing the mobility of people with PD.

In electronic musical instruments (EMIs), the concept of “sound sculpting” was proposed by Mulder, in which imaginary objects are manually sculpted to produce sounds, although promising has had some limitations: driven by pure intuition, only the objects’ geometrical properties were mapped to sound, while effort—which is often regarded as a key factor of expressivity in music performance—was neglected. The aim of this paper is to enhance such digital interactions by accounting for the perceptual measure of effort that is conveyed through well-established gesture-sound links in the ecologically valid conditions of non-digital music performances. Thus, it reports on the systematic exploration of effort in Dhrupad vocal improvisation, in which singers are often observed to engage with melodic ideas by manipulating intangible, imaginary objects with their hands. The focus is devising formalized descriptions to infer the amount of effort that such interactions are perceived to require and classify gestures as interactions with elastic versus rigid objects, based on original multimodal data collected in India for the specific study. Results suggest that a good part of variance for both effort levels and gesture classes can be explained through a small set of statistically significant acoustic and movement features extracted from the raw data and lead to rejecting the null hypothesis that effort is unrelated to the musical context. This may have implications on how EMIs could benefit from effort as an intermediate mapping layer and naturally opens discussions on whether physiological data may offer a more intuitive measure of effort in wearable technologies.

The aging population is now a global challenge, and impaired walking ability is a common feature in the elderly. In addition, some occupations such as military and relief workers require extra physical help to perform tasks efficiently. Robotic hip exoskeletons can support ambulatory functions in the elderly and augment human performance in healthy people during normal walking and loaded walking by providing assistive torque. In this review, the current development of robotic hip exoskeletons is presented. In addition, the framework of actuation joints and the high-level control strategy (including the sensors and data collection, the way to recognize gait phase, the algorithms to generate the assist torque) are described. The exoskeleton prototypes proposed by researchers in recent years are organized to benefit the related fields realizing the limitations of the available robotic hip exoskeletons, therefore, this work tends to be an influential factor with a better understanding of the development and state-of-the-art technology.

Electrical muscle stimulation (EMS) is widely used in rehabilitation and athletic training to generate involuntary muscle contractions. However, EMS leads to rapid muscle fatigue, limiting the force a muscle can produce during prolonged use. Currently available methods to monitor localized muscle fatigue and recovery are generally not compatible with EMS. The purpose of this study was to examine whether Doppler ultrasound imaging can assess changes in stimulated muscle twitches that are related to muscle fatigue from electrical stimulation. We stimulated five isometric muscle twitches in the medial and lateral gastrocnemius of 13 healthy subjects before and after a fatiguing EMS protocol. Tissue Doppler imaging of the medial gastrocnemius recorded muscle tissue velocities during each twitch. Features of the average muscle tissue velocity waveforms changed immediately after the fatiguing stimulation protocol (peak velocity: -38%, p = .022; time-to-zero velocity: +8%, p = .050). As the fatigued muscle recovered, the features of the average tissue velocity waveforms showed a return towards their baseline values similar to that of the normalized ankle torque. We also found that features of the average tissue velocity waveform could significantly predict the ankle twitch torque for each participant (R2 = 0.255–0.849, p < .001). Our results provide evidence that Doppler ultrasound imaging can detect changes in muscle tissue during isometric muscle twitch that are related to muscle fatigue, fatigue recovery, and the generated joint torque. Tissue Doppler imaging may be a feasible method to monitor localized muscle fatigue during EMS in a wearable device.

This paper presents the design, modeling, analysis, fabrication, and experimental characterization of the soft robotic ankle-foot orthosis (SR-AFO), which is a wearable soft robot designed for ankle assistance, and a pilot human study of its use. Using two novel pneumatically powered soft actuators, the SR-AFO is designed to assist the ankle in multiple degrees-of-freedom during standing and walking tasks. The flat fabric pneumatic artificial muscle (ff-PAM) contracts upon pressurization and assists ankle plantarflexion in the sagittal plane. The multi-material actuator for variable stiffness (MAVS) aids in supporting ankle inversion/eversion in the frontal plane. Analytical models of the ff-PAM and MAVS were created to understand how the changing of the design parameters affects tensile force generation and stiffness support, respectively. The models were validated by both finite element analysis and experimental characterization using a universal testing machine. A set of human experiments was performed with able-bodied participants to evaluate: (a) lateral ankle support during quiet standing, (b) lateral ankle support during walking over compliant surfaces, and (c) plantarflexion assistance during push-off in treadmill walking. Group results revealed increased lateral ankle stiffness during quiet standing with the MAVS active, reduced lateral ankle deflection while walking over compliant surfaces with the MAVS active, and reduced muscle effort in ankle platarflexors during 40–60% of the gait cycle with the dual ff-PAM active. The SR-AFO shows promising results in providing lateral ankle support and plantarflexion assistance with able-bodied participants, which suggests a potential to help restore the gait of impaired users in future trials.

Inclusive musical instruments benefit from incorporating wearable interfaces into digital musical instrument design, creating opportunities for bodily felt experiences and movement-based interactions. In this article, we discuss the evolution of our inclusive design approach behind the design and performance practices of three wearable musical instruments. By focusing on the embodied, somatic, and tacit dimensions of movement-based musical interaction, we evaluate these case studies, combining the third and first-person perspectives. The design and implementation of the wearable sensing, utilizing the additive manufacturing techniques, are discussed for each instrument and its performer in specific cases of musical expression. This article further discusses how our approach integrates music performance as a crucial step into design and evaluation, utilizing these performance practices and such collaborative settings for improved diversity and inclusion. Finally, we examine how our design approach evolves from user-centered design to more participatory practices, offering people with diverse abilities a shared music performance space.

Robotic assistive or rehabilitative devices are promising aids for people with neurological disorders as they help regain normative functions for both upper and lower limbs. However, it remains challenging to accurately estimate human intent or residual efforts non-invasively when using these robotic devices. In this article, we propose a deep learning approach that uses a brightness mode, that is, B-mode, of ultrasound (US) imaging from skeletal muscles to predict the ankle joint net plantarflexion moment while walking. The designed structure of customized deep convolutional neural networks (CNNs) guarantees the convergence and robustness of the deep learning approach. We investigated the influence of the US imaging’s region of interest (ROI) on the net plantarflexion moment prediction performance. We also compared the CNN-based moment prediction performance utilizing B-mode US and sEMG spectrum imaging with the same ROI size. Experimental results from eight young participants walking on a treadmill at multiple speeds verified an improved accuracy by using the proposed US imaging + deep learning approach for net joint moment prediction. With the same CNN structure, compared to the prediction performance by using sEMG spectrum imaging, US imaging significantly reduced the normalized prediction root mean square error by 37.55% ($ p $ < .001) and increased the prediction coefficient of determination by 20.13% ($ p $ < .001). The findings show that the US imaging + deep learning approach personalizes the assessment of human joint voluntary effort, which can be incorporated with assistive or rehabilitative devices to improve clinical performance based on the assist-as-needed control strategy.