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Wide-scale adoption of optoacoustic imaging in biology and medicine critically depends on availability of affordable scanners combining ease of operation with optimal imaging performance. Here we introduce LightSpeed: a low-cost real-time volumetric handheld optoacoustic imager based on a new compact software-defined ultrasound digital acquisition platform and a pulsed laser diode. It supports the simultaneous signal acquisition from up to 192 ultrasound channels and provides a hig-bandwidth direct optical link (2x 100G Ethernet) to the host-PC for ultra-high frame rate image acquisitions. We demonstrate use of the system for ultrafast (500Hz) 3D human angiography with a rapidly moving handheld probe. LightSpeed attained image quality comparable with a conventional optoacoustic imaging systems employing bulky acquisition electronics and a Q-switched pulsed laser. Our results thus pave the way towards a new generation of compact, affordable and high-performance optoacoustic scanners.

Wearable devices continuously gain their popularity due to flexibility and opportunity to enable more applications and services, in particular, in healthcare industry. Guarantying long-term operation for these devices is among the key challenges at the design stage. In this work, we propose a multi-source energy harvesting system to address this problem. The proposed solution is based on two technologies namely an Enzymatic Biofuel Cell (BFC) and a low-temperature gradient Thermoelectric Generator (TEG) which are capable of generating power from human perspiration and heat, respectively. Upon designing BFC, we designed a functional circuit that combines it with the TEG. The resulting BFC has an output voltage of 200 mV and a power of about 7 nW. An array of BFCs is used as a source for initial push to start up the internal logical control circuit of the DC-DC controller. The low-temperature gradient TEG with an output voltage ranging from 40 mV to 70 mV and a constant measured output power of 160 uW is used together with the BFCs for energy harvesting upon the initial starting of the DC-DC controller.

Ultrasound (US) is a widely used tool to observe musculoskeletal features during movement. US signals provide information about the instantaneous length and activation of muscles, and these signals are used for new prosthetic control strategies, to increase the performance of Human-Machine interfaces, or to improve muscle force predictions. However, existing commercial systems and research platforms are bulky, non-wearable, not supporting high frame rates, or lack configurability. Our work presents an US prototype meeting all key requirements to measure muscle activity during motion: our platform is open (providing access to raw data), flexible (operating in different modalities and channel count), it features wireless connectivity (supporting high frame rates> 100 Hz) and supports low power consumption (

We demonstrate the feasibility of a compact real-time 3D optoacoustic (OA) imager employing a novel low-cost software-defined ultrasound digital acquisition platform. It supports simultaneous signal acquisition from up to 192 ultrasound channels and a direct optical link (2x 100G Ethernet) to the host-PC for high-frame-rate image acquisitions. Real-time 3D imaging experiments with light-absorbing phantoms and the wrist of a healthy volunteer are reported. These results pave the way toward a new generation of compact, affordable, and flexible hand-held OA scanners.

There is recent experimental evidence that sarcomere strain behavior is highly heterogeneous across and between muscle structures. Hence, considering the hierarchical architecture of muscles, also the behavior of all acting muscle substructures is effected. However, typical investigations are limited to ex-vivo experiments or pose serious limitations for in-vivo studies. In this work, we investigate in-vivo length changes in human muscle fascicles by means of non-invasive ultrafast ultrasound. To this end, we employ a research ultrasound system and a linear array transducer to image, in plane-wave mode, medial gastrocnemius muscles during electrically-stimulated contractions. The ultrasound-based approach presented in this study allows to measure strain distributions within muscle fascicles during contractions, where the sub-fascicle structures exhibit heterogeneous behaviors.

Until now direct localization of motor endplates for any arbitrary muscle structure was reserved to cadaver studies or restricted to specific muscles in-vivo. Utilizing ultrafast ultrasound we report a versatile in-vivo method for the detection of motor endplate zones. To achieve this goal, we employ a research ultrasound system with a linear array transducer probe to record ultrasound images of electrically-stimulated medial gastrocnemius muscles. An optical flow speckle tracking algorithm is used to track the points along a single fascicle. We localize motor endplates at intersection points where mechanical contraction waves diverge bidirectionally towards the fiber ends. Contrary to common experimental methods, our proposed ultrafast ultrasound-based approach allows to localize motor endplates also in deep and pennate muscles in-vivo. These results open up new applications for ultrasound in neuromuscular research.

Thermoelectric energy harvesting (TEH) is a promising technology enabling the self-sustainable operation of ultra low-power sensing devices performing monitoring tasks. Conventional TEH research mainly focuses on the improvements of the material properties (i.e thermoelectric figure of merit ZT) and thermoelectric module (TEM) geometry. However, enhanced performance of the thermoelectric generator (TEG) can not be practically achieved without optimal integration of the novel TEM with the DC-DC converter. The power converter, having its own input impedance requirements and conversion efficiency curve, may keep the operation point of TEG far from the maximum power point of TEM, leading to power loss. Furthermore, since the physical processes in the thermoelectric transducer are coupled with the electrical processes in the DCDC converter, both components should be analyzed together to achieve the best harvesting performance. Given the system complexity, an accurate simulation model is required to estimate the output power and make an optimal system design. We report on a simulation approach for low temperature gradient TEG that accounts for both the thermoelectric and the power conversion processes. The proposed approach was validated on the TEG testbed by imitating the realistic ambient conditions for thermoelectric transducer connected to a commercial off-the-shelf DC-DC converter. Experimental results are characterized by 9% mean percentage error of power estimation which outperforms the methods based on conventional TEG representations.

Internet of Things (IoT) and wearable sensing paradigm assume the sensing devices are available 24/7 and can be accessed from anywhere. This vision implies strict requirements to the power supply and energy harvesting which are expected to guarantee ‘perpetual’ operation of IoT devices. This paper reports on modelling and experimental verification of low temperature gradient thermoelectric generator. Obtained under the conditions of low gradient temperature approximation, the model accounts for the key physical phenomena and enables the accurate output power calculations using a closed-form expression. We perform a comparative study on the state-of-the-art models against the obtained solution and show the simplicity and performance of the proposed approach. For demonstrating practical feasibility of the model, we develop an experimental testbed consisting of the power generator, temperature control and data acquisition units. Experimental results demonstrate the average error 5.5 % which improves the state-of-the-art results.