Paralysed man can feel objects through another person's hand Keith Thomas, a man in his 40s with no sensation or movement in his hands, is able to feel and move objects by controlling another person's hand via a brain implant. The technique might one day even allow us to experience another person's body over long distances. Keith Thomas (right) was able to control another person's hand A man with paralysis has been able to move and sense another person's hand as if it were his own, thanks to a new kind of "telepathic" brain implant. "We created a mind-body connection between two different individuals," says Chad Bouton at the Feinstein Institutes for Medical Research in New York state. The approach could be used as a form of rehabilitation after spinal cord injury, allowing people with paralysis to work together, and may one day even allow people to share experiences remotely, says Bouton.

In this paper, we present a general specification for Functional Effects Models, which use Machine Learning (ML) methodologies to learn individual-specific preference parameters from socio-demographic characteristics, therefore accounting for inter-individual heterogeneity in panel choice data. We identify three specific advantages of the Functional Effects Model over traditional fixed, and random/mixed effects models: (i) by mapping individual-specific effects as a function of socio-demographic variables, we can account for these effects when forecasting choices of previously unobserved individuals (ii) the (approximate) maximum-likelihood estimation of functional effects avoids the incidental parameters problem of the fixed effects model, even when the number of observed choices per individual is small; and (iii) we do not rely on the strong distributional assumptions of the random effects model, which may not match reality. We learn functional intercept and functional slopes with powerful non-linear machine learning regressors for tabular data, namely gradient boosting decision trees and deep neural networks. We validate our proposed methodology on a synthetic experiment and three real-world panel case studies, demonstrating that the Functional Effects Model: (i) can identify the true values of individual-specific effects when the data generation process is known; (ii) outperforms both state-of-the-art ML choice modelling techniques that omit individual heterogeneity in terms of predictive performance, as well as traditional static panel choice models in terms of learning inter-individual heterogeneity. The results indicate that the FI-RUMBoost model, which combines the individual-specific constants of the Functional Effects Model with the complex, non-linear utilities of RUMBoost, performs marginally best on large-scale revealed preference panel data.

Hand exoskeletons have significant potential in labor-intensive fields by mitigating hand grip fatigue, enhancing hand strength, and preventing injuries.However, most traditional hand exoskeletons are driven by motors whose output force is limited under constrained installation conditions. In addition, they also come with the disadvantages of high power consumption, complex and bulky assistive systems, and high instability.In this work, we develop a novel hand exoskeleton integrated with magnetorheological (MR) clutches that offers a high force-to-power ratio to improve grip endurance. The clutch features an enhanced structure design, a micro roller enhancing structure, which can significantly boost output forces. The experimental data demonstrate that the clutch can deliver a peak holding force of 380 N with a consumption of 1.48 W, yielding a force-to-power ratio of 256.75N/W, which is 2.35 times higher than the best reported actuator used for hand exoskeletons. The designed MR hand exoskeleton is highly integrated and comprises an exoskeleton frame, MR clutches, a control unit, and a battery. Evaluations through static grip endurance tests and dynamic carrying and lifting tests confirm that the MR hand exoskeleton can effectively reduce muscle fatigue, extend grip endurance, and minimize injuries. These findings highlight its strong potential for practical applications in repetitive tasks such as carrying and lifting in industrial settings.

In the 2016 movie Passengers, the crew of a spacecraft bound for a distant planet had access to a scanning chamber known as Autodoc that could instantly diagnose their medical problems and even predict the time of their death. I'm reminded of this, and countless other sci-fi plots, as I strip off my robe and step semi-naked into the gleaming capsule of the Neko Body Scan. Like Autodoc, it promises to conduct a comprehensive examination of my health – inside and out – within minutes, and, while unable to estimate the timing of my demise (yet), it can identify whether I'm at imminent or future risk of developing some of the biggest killers and causes of chronic ill health. Healthy as I may feel on the outside, the prospect of learning whether there is some hidden nastiness lurking on my health horizon, feels too tempting to refuse. The doors of the pod slide shut, and a soothing female voice instructs me to close my eyes and keep still.

Granular jamming has recently become popular in soft robotics with widespread applications including industrial gripping, surgical robotics and haptics. Previous work has investigated the use of various techniques that exploit the nature of granular physics to improve jamming performance, however this is generally underrepresented in the literature compared to its potential impact. We present the first research that exploits vibration-based fluidisation actively (e.g., during a grip) to elicit bespoke performance from granular jamming grippers. We augment a conventional universal gripper with a computer-controllled audio exciter, which is attached to the gripper via a 3D printed mount, and build an automated test rig to allow large-scale data collection to explore the effects of active vibration. We show that vibration in soft jamming grippers can improve holding strength. In a series of studies, we show that frequency and amplitude of the waveforms are key determinants to performance, and that jamming performance is also dependent on temporal properties of the induced waveform. We hope to encourage further study focused on active vibrational control of jamming in soft robotics to improve performance and increase diversity of potential applications.

Fruit harvesting has recently experienced a shift towards soft grippers that possess compliance, adaptability, and delicacy. In this context, pneumatic grippers are popular, due to provision of high deformability and compliance, however they typically possess limited grip strength. Jamming possesses strong grip capability, however has limited deformability and often requires the object to be pushed onto a surface to attain a grip. This paper describes a hybrid gripper combining pneumatics (for deformation) and jamming (for grip strength). Our gripper utilises a torus (donut) structure with two chambers controlled by pneumatic and vacuum pressure respectively, to conform around a target object. The gripper displays good adaptability, exploiting pneumatics to mould to the shape of the target object where jamming can be successfully harnessed to grip. The main contribution of the paper is design, fabrication, and characterisation of the first hybrid gripper that can use granular jamming in free space, achieving significantly larger retention forces compared to pure pneumatics. We test our gripper on a range of different sizes and shapes, as well as picking a broad range of real fruit.

Sony's holding its Technology Day event to show off what it's been working on in its R&D labs, and this year, we got some great visuals of tech the company's been working on. Amidst the rehashes of the PS5's haptics and 3D audio and a demo reel of Sony's admittedly awesome displays for making virtual movie sets, we got to see a robot hand that Sony said could figure out grip strength depending on what it was picking up, a slightly dystopian-sounding "global sensing system," and more. Perhaps the most interesting thing Sony showed off was a headset that featured OLED displays with "4K-per-inch" resolution. While the headset Sony used in its presentation was very clearly something intended for lab and prototype use, the specs Sony laid out for the panels were reminiscent of the rumors swirling around the PlayStation VR 2. They don't exactly line up, though; Sony said the headset it showed off was 8K, given the 4K display per eye, and the PS VR 2 will supposedly only be 4K overall with 2000 x 2040 pixels per eye. Still, it's exciting that Sony is working on VR-focused panels, along with latency reduction tech for them.

Elderly people living today are fitter and healthier than they were 30 years ago, according to a study by Finnish researchers. As a result of better nutrition, hygiene and healthcare people between 75 and 80 now walk, on average, almost 1mph faster than they did in 1990. The oldest members of society also have greater leg and grip strength in the modern era, as well as improved reaction speed, verbal fluency, reasoning and memory. Finnish researchers compared data on 500 people born between 1910 and 1914, who were tested between 1989 and 1990, with 726 people born in 1938 or 1939 and tested in 2017 and 2018. The same tests were administered to both groups and assessed physical state as well as cognitive function.

When she was a practicing occupational therapist, Elizabeth Fain started noticing something odd in her clinic: Her patients were weak. More specifically, their grip strengths, recorded via a hand-held dynamometer, were "not anywhere close to the norms" that had been established back in the 1980s. Fain knew that physical activity levels and hand-use patterns had changed a lot since then. Jobs had become increasingly automated, the professional and service sectors had grown, all sorts of measures of physical activity (like the likelihood that a child walks to school1) had declined, and the personal computer age had dawned. But to see the numbers decline so steeply and quickly was still a surprise, and not just to her.

Grip strength, as well as walking speed and gait length, can be indicators of a person's physical and mental health. A variety of conditions and treatments can be monitored from the grip strength, but such measurements are typically only performed infrequently at the doctor's office. IBM Research has just developed a sensor that is attached to a fingernail on the index finger, that can measure the finger's motion and from that figure out the grip strength. The engineers were originally motivated to create a device that can help with monitoring of Parkinson's patients, as changes in a medication regimen should normally be accounted by changes in symptoms. Since most Parkinson's sufferers are older folks, skin-based sensors can be not as accurate and may lead to unwanted infections, but the fingernail is safer in this respect and provide a great deal of information about a person's daily activities.