Grip strength, a crucial indicator of overall health, is linked to aging, diseases, nutrition, and rehabilitation progress. Existing hospital instruments and commercial dynamometers often lack the sensitivity and small size needed for infants and rehabilitation patients. This necessitates a personalized, simple, inexpensive, and painless method for long-term grip strength monitoring, especially given the strong correlation between reduced grip strength and increased cardiovascular mortality risk. This research introduces a smart ball sensor designed to address this unmet need. Inspired by 3D spherical designs and laser kirigami techniques, the sensor integrates a soft elastic ball base, graphene-based spiral sensors, a central pill shell containing electronics, and a sealing layer. The 3D design, coupled with wireless transmission to a mobile phone, offers portability and user convenience. FEA was used to model the hand-ball contact area's influence on grip strength, improving measurement accuracy. The sensor's performance was validated in adults and children against hospital and household grip measurement devices.

The literature extensively highlights the importance of grip strength as a prognostic indicator of various health conditions, including cardiovascular disease and mortality. Studies demonstrate a strong correlation between decreased grip strength and increased risk of cardiovascular events and mortality across diverse populations. However, current grip strength measurement tools often lack the sensitivity and portability needed for personalized long-term monitoring, especially in vulnerable populations like infants and rehabilitation patients. This gap motivated the development of the novel smart ball sensor described in this study.

The smart ball sensor's fabrication involved several key steps: 1. **Graphene-based spiral sensor fabrication:** A spiral-sensing unit was created by direct laser patterning of graphene on a polyimide film. Optimized laser parameters (lower laser speed of 1%, power of 0.3%, and PPI of 400) were employed to achieve a low electrical resistance (4.59 kΩ cm⁻¹). A protective layer of PDMS was applied to prevent graphene loss. The spiral sensor's piezoresistive properties allow it to detect resistance changes due to deformation, enabling grip strength measurement. 2. **Smart ball sensor assembly:** The electronics (power system, Bluetooth, and control system) were housed in a transparent pill shell at the center of a soft, elastic PDMS ball. The spiral sensor was precisely integrated onto the ball's surface. A temperature-sensitive layer was added for visual feedback. The design ensures a comfortable and convenient user experience. 3. **Finite-element analysis (FEA):** FEA simulations were conducted to analyze the impact of the contact area between the hand and the ball on grip strength readings. A 2D model using a cylindrical indenter and a 3D model simulating handgrip were used to establish relationships between compression force, strain on the spiral sensor, and contact area. These models informed the development of a refined equation for calculating grip strength, incorporating both force and contact area. 4. **In vitro validation:** The accuracy and reliability of the sensor were validated using in vitro experiments. The accuracy was defined as 1 - [(Fmon - Freal)/Freal], where Fmon is the grip strength derived from the sensor and Freal is the actual grip strength obtained during indentation tests. The performance of the sensor was compared against both hospital grip instruments and a household dynamometer in both adult and pediatric populations. The experiments involved indentation tests to establish the relationship between grip strength and resistance change, and on-body validation tests on adults and children to compare with standard methods.

The smart ball sensor demonstrated several key advantages: 1. **High Sensitivity and Accuracy:** The sensor showed high sensitivity to even small deformations, making it suitable for measuring the grip strength of infants and patients with weak grips. The incorporation of the contact area into the grip strength calculation significantly improved the accuracy of the measurements, with an 11.18% improvement observed compared to a model that did not consider contact area. 2. **Personalized and Customizable Design:** The 3D design, soft elastic material, and variable sizes allow the sensor to be customized for various hand sizes, offering personalized grip strength measurement. The addition of a temperature-sensitive layer provides an engaging visual element, especially beneficial for children. 3. **Wireless and Portable Design:** The wireless transmission of data via Bluetooth to a mobile phone eliminates the need for cumbersome equipment, making the sensor convenient for long-term monitoring in daily life. This is a significant advancement over traditional bulky hospital instruments. 4. **Robust and Reliable Performance:** The sensor demonstrated stable and repeatable performance across multiple compression cycles. The FEA modelling helped to significantly improve the accuracy of measurements by accounting for the 3D contact area between the hand and the ball. The use of graphene provided superior material properties including high electrical conductivity. 5. **Effective across Populations:** The on-body validation tests demonstrated high accuracy and reliability when compared to gold-standard hospital instruments and household dynamometers for both adults and children. It was found to be effective in measuring grip strength from children as young as 1 year of age.

The development of this smart ball sensor addresses the significant limitations of existing grip strength measurement tools. Its sensitivity, portability, and personalized design make it suitable for long-term monitoring across diverse populations, particularly infants and rehabilitation patients. The incorporation of FEA modelling to account for the 3D contact area between hand and ball represents a novel and significant contribution to the field, significantly enhancing the accuracy of grip strength measurements. The high correlation between the sensor's readings and gold-standard methods validates its reliability and clinical potential. This technology holds promise for improved healthcare management, early disease detection, and personalized rehabilitation monitoring.

This study successfully demonstrated the feasibility and effectiveness of a novel smart ball sensor for personalized long-term grip strength monitoring. The sensor's unique design, incorporating laser kirigami of graphene, FEA-informed calibration, and wireless data transmission, addresses current limitations in grip strength assessment. Future research could focus on expanding the sensor's functionality, such as integrating additional health parameters, and exploring its application in broader clinical settings.

While the study demonstrated promising results, some limitations should be acknowledged. The in vitro validation, while comprehensive, did not fully encompass the wide range of real-world handgrip conditions. Further studies are needed to evaluate the sensor's long-term stability and durability under prolonged usage. Additionally, the current model primarily focuses on vertical compression; future research should investigate the impact of other loading directions and refine the equation accordingly.